TYPE,NAME,INFOHASH,SIZEBYTES,MIRRORS,DOWNLOADERS,TIMESCOMPLETED,DATEADDED,DATEMODIFIED
Paper,"A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics",8e8a341c6948e0f1e4f70fd0386aa5a408bdb07f,70368,0,0,72,1398650160,0
Paper,"Optimally Fuzzy Temporal Memory",d9fd9cf32c98c6065ee9f1bcfcefe1eb31bd0153,674312,0,0,36,1398650160,0
Paper,"Fast Generalized Subset Scan for Anomalous Pattern Detection",d0b31ee6d5931a855f800299083e6e7aa3941f17,2755573,0,0,33,1398650160,0
Paper,"A Risk Comparison of Ordinary Least Squares vs Ridge Regression",6c43ba1182eb57633acdfd0ff0dff42d96d34abc,189762,0,0,48,1398650160,0
Paper,"QuantMiner for Mining Quantitative Association Rules",e2d6ac42e4b4e038afc01aab5c8419bf75f3f85a,319048,0,0,46,1398650160,0
Paper,"Consistent Selection of Tuning Parameters via Variable Selection Stability",56b0927f2f3ac7afcd7813e81edcd542582667f2,251371,0,0,31,1398650160,0
Paper,"Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows",b863eefbdcc6404f3be91c3d095435a1b96f5b70,373945,0,0,34,1398650160,0
Paper,"Machine Learning with Operational Costs",15efe86562dcb326f78d160eb9bd2526a5e4a431,824494,0,0,48,1398650160,0
Paper,"Random Walk Kernels and Learning Curves for Gaussian Process Regression on Random Graphs",ace4c246b027b1f9b6e8c1754308eb1cda6c898e,517105,0,0,31,1398650160,0
Paper,"Learning Bilinear Model for Matching Queries and Documents",afbdf200cac57471377e6b8398f4ce71159f7425,350476,0,0,32,1398650160,0
Paper,"Stress Functions for Nonlinear Dimension Reduction, Proximity Analysis, and Graph Drawing",78f800a01c5a4f423e355d96868684c18ca6bd37,593035,2,0,121,1398650160,0
Paper,"The Rate of Convergence of AdaBoost",ff0b5f0827dd3d3c6d8cda578c71eb14e96e72fa,314876,0,0,32,1398650161,0
Paper,"The CAM Software for Nonnegative Blind Source Separation in R-Java",84f3cc29df08fb56897e273e4bb9ddb88826ddcd,637864,0,0,56,1398650161,0
Paper,"Learning Theory Approach to Minimum Error Entropy Criterion",4be84fdbfbea612cf6152061b6e9bcabdb08d727,194956,0,0,37,1398650161,0
Paper,"Segregating Event Streams and Noise with a Markov Renewal Process Model",914bd8a803ca859ce68c8f590a0c201bc4f392c5,744310,0,0,36,1398650161,0
Paper,"Message-Passing Algorithms for Quadratic Minimization",264e2cd52f86ee907b6b4f3d433b2c5e21cb6c9c,264041,0,0,45,1398650161,0
Paper,"Semi-Supervised Learning Using Greedy Max-Cut",86353516df61c721c88727c5e08102d62f5bb0c8,1493677,0,0,34,1398650161,0
Paper,"A Theory of Multiclass Boosting",345fadbd720a0c19cceae72cd7bcbf3097e4709d,2956784,0,0,37,1398650161,0
Paper,"Multicategory Large-Margin Unified Machines",f974c362bb4dd7389d57ca440ce30cbe6d4c1da2,612665,0,0,27,1398650161,0
Paper,"Construction of Approximation Spaces for Reinforcement Learning",84509a4a078fa60891ac06266b40a5e462e5aa21,778545,0,0,37,1398650161,0
Paper,"Classifier Selection using the Predicate Depth",214e8915b8577100002a71fa3d47a86b1a029909,243217,0,0,32,1398650161,0
Paper,"Derivative Estimation with Local Polynomial Fitting",229007c16859c349db75d9291007dc6d9164a3d2,590779,0,1,10,1398650161,0
Paper,"PC Algorithm for Nonparanormal Graphical Models",4b00a46b4e282e2374c3828c5c0afe0d52cf106e,177771,2,0,61,1398650161,0
Paper,"Distribution-Dependent Sample Complexity of Large Margin Learning",f6d27117b042204a40e7e190329034d663c1b108,335735,0,0,30,1398650161,0
Paper,"Multi-Stage Multi-Task Feature Learning",3e14552bdb167b2b7a22de8cb7dd0c96de0097f7,303999,0,0,38,1398650161,0
Paper,"Sparse Single-Index Model",61059f50d1a161c60b8c1ea44ad0e8d3090bdd1b,321557,0,0,37,1398650161,0
Paper,"Random Spanning Trees and the Prediction of Weighted Graphs",66ed1109aa9929c9eb1c24516b32955b7150b2f3,369540,2,0,43,1398650161,0
Paper,"Training Energy-Based Models for Time-Series Imputation",0c162286c06b90e38d7218d05b5112eda0f1a1c1,419200,0,0,38,1398650162,0
Paper,"Greedy Feature Selection for Subspace Clustering",b796e5aa53966f8ce62ee9a365f081df7d7be9cf,956724,0,0,31,1398650162,0
Paper,"Query Induction with Schema-Guided Pruning Strategies",4217eafb21e63fbea07b82c407c23b1348574bd2,424419,0,0,36,1398650162,0
Paper,"Convex and Scalable Weakly Labeled SVMs",eb3bb1fc339cbee797f5d00a54ab05711852cc34,1026847,0,0,30,1398650162,0
Paper,"MLPACK: A Scalable C++ Machine Learning Library",421ca1dc8f130655ce397a1c8debc783c02cbe36,68230,0,0,54,1398650162,0
Paper,"Cluster Analysis: Unsupervised Learning via Supervised Learning with a Non-convex Penalty",993186991db28b9dc900b79d8f0ebadd2cbc52bd,240325,0,0,45,1398650162,0
Paper,"Efficient Active Learning of Halfspaces: An Aggressive Approach",d7c4adf97cb54719016ab5fd79b1b371a84515b5,2894421,0,0,29,1398650162,0
Paper,"A Binary-Classification-Based Metric between Time-Series Distributions and Its Use in Statistical and Learning Problems",c2d3ecf0482fc560115374b49811ec987841f1f0,207382,0,0,33,1398650162,0
Paper,"Nonparametric Sparsity and Regularization",e7495e1384e497a1fd0abb0681d5c385501c24aa,612850,0,0,34,1398650162,0
Paper,"Language-Motivated Approaches to Action Recognition",0ec67ef0c5b2bd52c368fefa0adcd4d1c1acb6a4,1740589,0,0,49,1398650162,0
Paper,"A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion",9264f7bc4398f050d9bcf4de98fae7ea9084b21f,269057,0,0,26,1398650162,0
Paper,"Finding Optimal Bayesian Networks Using Precedence Constraints",849050c3f0bc3e01c779052bdf08fa154bc15035,343106,0,0,28,1398650162,0
Paper,"Risk Bounds of Learning Processes for Lvy Processes",6c4bc5c78e4ef49baa1f149efc17be6043c6ec80,273289,0,0,34,1398650162,0
Paper,"GURLS: A Least Squares Library for Supervised Learning",b4c0f6ea0506eeff72c634ec5fda84d1642e7bd2,76030,0,0,40,1398650162,0
Paper,"Bayesian Canonical Correlation Analysis",eee108e08076ee344aa51cdfc9734c797120602e,515468,0,0,36,1398650162,0
Paper,"Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels",8e407b6e1ef0d8ab9719e4370dab098e5a91f3df,329174,0,0,42,1398650163,0
Paper,"Dimension Independent Similarity Computation",575f027a9c75e3447aae3454e06ad507d974b218,190022,0,0,29,1398650163,0
Paper,"Ranking Forests",647b5acb68f125d42953e0a3b64618d8e49ef188,1006171,0,0,30,1398650163,0
Paper,"Pairwise Likelihood Ratios for Estimation of Non-Gaussian Structural Equation Models",a7fefbb22f4272f4874df581d31c9f4c999d6fe3,1163343,0,0,38,1398650163,0
Paper,"On the Convergence of Maximum Variance Unfolding",7724e3ac4793964830bbb1197c1d4b8055077eb4,219460,0,0,32,1398650163,0
Paper,"Differential Privacy for Functions and Functional Data",7c41af39ec87531026ca7613e292cb9fbadcfbb9,314746,0,0,32,1398650163,0
Paper,"Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems",2ba79fabb855edbf6822f941d893e5d59491f585,535153,0,0,46,1398650163,0
Paper,"Divvy: Fast and Intuitive Exploratory Data Analysis",f336d8efafd0aaeae8b622e29b1b95bf3d22597d,276717,1,0,37,1398650163,0
Paper,"CODA: High Dimensional Copula Discriminant Analysis",65253d2fb4e703172a02fed3a3370fdc617e22ca,399297,0,0,30,1398650163,0
Paper,"Using Symmetry and Evolutionary Search to Minimize Sorting Networks",681dd00655f3a45ecf9a46a8bf5f3602bfe9292a,507961,0,0,34,1398650163,0
Paper,"A Framework for Evaluating Approximation Methods for Gaussian Process Regression",6d758dd0a91c0b6fd19b560b21f7af83e60f9de3,331766,0,0,36,1398650163,0
Paper,"Bayesian Nonparametric Hidden Semi-Markov Models",b36dbb5196a73a82affdf3e546b7fa51ba60bb52,586134,0,0,49,1398650163,0
Paper,"Stochastic Variational Inference",20a05bcb487cd0d3677f086c964d3e0059537dee,397775,0,0,33,1398650163,0
Paper,"Comment on "Robustness and Regularization of Support Vector Machines" by H. Xu et al. (Journal of Machine Learning Research, vol. 10, pp. 1485-1510, 2009)",d3fa0705e62cc295e0d843df0907221f026ef597,41090,0,0,28,1398650163,0
Paper,"On the Mutual Nearest Neighbors Estimate in Regression",f4682214947aed9fd99205372630202aa1ae315f,142780,0,0,26,1398650163,0
Paper,"Orange: Data Mining Toolbox in Python",78e7fe1bb1b432f24c4e0226a25d02c2a8ca60c2,63403,1,0,188,1398650164,0
Paper,"Multivariate Convex Regression with Adaptive Partitioning",0e27179d76982da01c8341a89719f8f227ee9ae4,1729398,0,0,42,1398650164,0
Paper,"Feature Selection with Ensembles, Artificial Variables, and Redundancy Elimination(Special Topic on Model Selection)",a6f1ed86b6f94fa6834470612936ff64da1a8ae9,200941,0,0,33,1398650164,0
Paper,"Dynamic Affine-Invariant Shape-Appearance Handshape Features and Classification in Sign Language Videos",6a0ba63fce87c30813082fc424ed2328836b7bbf,3980870,0,0,35,1398650164,0
Paper,"Distributions of Angles in Random Packing on Spheres",2cef7ef506fad29fe636bc6c67d7dd3045bc011b,276012,0,0,36,1398650164,0
Paper,"Alleviating Naive Bayes Attribute Independence Assumption by Attribute Weighting",13a66360265771ac37ad4fe29881cebb33a764e7,442448,0,0,34,1398650164,0
Paper,"Greedy Sparsity-Constrained Optimization",3586e9c854fd5ee46fee11267c739f656e5cbafc,362499,0,0,32,1398650164,0
Paper,"Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem",9e40b4952217ba1d7e8995563dfa9bb7ed456506,200238,0,0,27,1398650164,0
Paper,"The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs",0e020decfe281838b7b7509664c72c4fc51c4cb0,1532710,0,0,32,1398650164,0
Paper,"BudgetedSVM: A Toolbox for Scalable SVM Approximations",b15610978ec89ae1a633e4f4a9dca94a0e22815a,74781,0,0,28,1398650164,0
Paper,"Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections",07eaf4e61b499e738b1283822e747bdb6c822993,325553,0,0,32,1398650164,0
Paper,"Sparse Activity and Sparse Connectivity in Supervised Learning",4185bdbd907ae4cfa646f255c79f7382fdb0b3a6,526246,0,0,34,1398650164,0
Paper,"Classifying With Confidence From Incomplete Information",1626b334c3611184069e15f2d4a38d284c559405,1091459,0,0,34,1398650164,0
Paper,"Learning Theory Analysis for Association Rules and Sequential Event Prediction",58947cb7a9cae9ed60c2a86027f988d5c645272f,1985899,0,0,31,1398650164,0
Paper,"Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality",6d1c604147dd7bd88d31a8ca7415bc63ea71f2f5,327203,0,0,30,1398650164,0
Paper,"Fast MCMC Sampling for Markov Jump Processes and Extensions",f25629fe4d9c718ae5c024e4c4abe514985c4429,393640,0,0,30,1398650164,0
Paper,"A Least-squares Approach to Direct Importance Estimation",1052dae93cf2dfdee284c06e36384b0c120508ee,849232,0,0,38,1398650164,0
Paper,"One-shot Learning Gesture Recognition from RGB-D Data Using Bag of Features",14e4b3fffcbf8c4e2497ab35c3ea0c946d16b433,2952074,0,0,35,1398650164,0
Paper,"Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors",7cb135851a967364a44b500ef1382524390f5fd7,174470,0,0,52,1398650165,0
Paper,"Quasi-Newton Method: A New Direction",56fa80cbecf20bd53066d0cbd4b84d5224236912,297809,0,0,48,1398650165,0
Paper,"Data-driven Calibration of Penalties for Least-Squares Regression",fe4da40a6b0027d3ae8c9531cbe9224014e56af1,262751,0,0,33,1398650165,0
Paper,"Analysis of Perceptron-Based Active Learning",dcff855a3bbf542f6784ee85764cb96ac13c6e55,176009,0,0,39,1398650165,0
Paper,"Properties of Monotonic Effects on Directed Acyclic Graphs",78411eabf3e1484d3bd97b2b03fe8cbfb3316859,181590,0,0,30,1398650165,0
Paper,"CarpeDiem: Optimizing the Viterbi Algorithm and Applications to Supervised Sequential Learning",59c4f8d17a1b6bf8cb10135b87dbd2309ef7c188,1149428,0,0,35,1398650165,0
Paper,"Truncated Power Method for Sparse Eigenvalue Problems",807e9ca4e5e7303780944acba61182f8f81717d0,645499,0,0,45,1398650165,0
Paper,"Sparse Matrix Inversion with Scaled Lasso",46e403867091a86d6ccc31f9808beedf52adf803,313345,0,0,28,1398650165,0
Paper,"Robustness and Regularization of Support Vector Machines",c213084c164b0d7f80c6b816ceee199b697e2dc3,189265,0,0,46,1398650165,0
Paper,"Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models",c039fcb1cac9bff23da0ac663e0d1bee6f4aae9c,564841,0,0,29,1398650165,0
Paper,"Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions",2a0b3a40040592aef9c4c747bd0e4997360d8e3d,314362,0,0,45,1398650165,0
Paper,"Keep It Simple And Sparse: Real-Time Action Recognition",0216db9a867c799c7da89b3a052c4a6293b4d7c8,1869241,0,0,50,1398650165,0
Paper,"Online Learning with Sample Path Constraints",03465825ecd565378cacfa979f041b0d8f2593be,192136,0,0,39,1398650165,0
Paper,"Reinforcement Learning in Finite MDPs: PAC Analysis",2cd4976d263fd6e5d4b1f8e2f22438b1b82e9cde,272554,0,0,36,1398650165,0
Paper,"A Survey of Accuracy Evaluation Metrics of Recommendation Tasks",b31f8310f96f1b3563bdb7a3d11878711b63b000,267620,0,0,32,1398650165,0
Paper,"Sub-Local Constraint-Based Learning of Bayesian Networks Using A Joint Dependence Criterion",3cc32b00695bb7bb972bbcdf8e75fb666463db86,614808,0,0,49,1398650166,0
Paper,"Global Analytic Solution of Fully-observed Variational Bayesian Matrix Factorization",14361906a005e3523b5470dafe249c2b873cdcca,507623,0,0,36,1398650166,0
Paper,"Stable and Efficient Gaussian Process Calculations",e57b2069c47c25a5bb00f886c925a305eceef20d,246968,0,0,29,1398650166,0
Paper,"Gaussian Kullback-Leibler Approximate Inference",92db2e5b8a0e24d94e5234e948049f6bc6cc9438,922451,0,0,35,1398650166,0
Paper,"Similarity-based Clustering by Left-Stochastic Matrix Factorization",f2dec4ca78971464b95b3abad3505fd03b5c2cc1,317135,0,0,27,1398650166,0
Paper,"Hybrid MPIOpenMP Parallel Linear Support Vector Machine Training",cadd0708c887e5e73fceb9cbec3123f5e6150822,133809,0,0,33,1398650166,0
Paper,"Deterministic Error Analysis of Support Vector Regression and Related Regularized Kernel Methods",1ad9699408b1524336afed9ad9a4d04295f6b691,163771,0,0,34,1398650166,0
Paper,"Large-scale SVD and Manifold Learning",57bd784d8ae732ff60e330239ff43ef62c2c3abc,4354683,0,0,28,1398650166,0
Paper,"Algorithms for Discovery of Multiple Markov Boundaries",68408d7bda78720ac26f8e057d8f8cde9abd5718,831150,0,0,38,1398650166,0
Paper,"Similarity-based Classification: Concepts and Algorithms",bcdd07948277fb3b20b1727ef2104107a05995eb,8741840,0,0,55,1398650166,0
Paper,"Prediction With Expert Advice For The Brier Game",5839ddb77c57af03dd14e4b9da0cd7ce727664ae,1338728,0,0,32,1398650166,0
Paper,"The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models",3f017fc1ceb243bf9c912df7e9a81da265ff1122,676531,0,0,47,1398650166,0
Paper,"Generalized Spike-and-Slab Priors for Bayesian Group Feature Selection Using Expectation Propagation",e5b57ee36c72734c8692c50356be672c12d35fed,1656995,0,0,31,1398650166,0
Paper,"Estimating Labels from Label Proportions",8dc40264fcbfb8c203cb0fd94fa207d0162c7c53,390111,0,0,31,1398650166,0
Paper,"Robust Process Discovery with Artificial Negative Events(Special Topic on Mining and Learning with Graphs and Relations)",25d166d65b19493fe44c29af341d71589179b2d3,499128,0,0,41,1398650166,0
Paper,"Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection",2a95276bf51b951ddafdf9681ff18ecba03b92ea,3239712,0,0,35,1398650166,0
Paper,"Lovasz theta function, SVMs and Finding Dense Subgraphs",67debaedcfd2ce2480e419ce3a44156135d38b8a,730305,0,0,32,1398650166,0
Paper,"Perturbation Corrections in Approximate Inference: Mixture Modelling Applications",503dcb099f984a19d76edd8303fa9915f4894edb,863458,0,0,32,1398650166,0
Paper,"Stationary-Sparse Causality Network Learning",7a3ecd1c3f81fb6a0dda78bc1c2ff8d87758d759,416785,0,0,27,1398650166,0
Paper,"Tapkee: An Efficient Dimension Reduction Library",ec09477ac7af2e3bb135819d83619f1a4fcc0c37,598465,0,0,27,1398650167,0
Paper,"Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising",76b9a4b27cd4f3436b349e438be1c1663abeebea,1394801,0,0,44,1398650167,0
Paper,"Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data(Machine Learning Open Source Software Paper)",e684c0edea6d7ec83fb16980bdcb7e502adef004,37216,8,0,199,1398650167,0
Paper,"Variational Algorithms for Marginal MAP",ef3fd853ccf3a0c8331ab9908d3e4befabf5ef80,665799,0,0,39,1398650167,0
Paper,"Distributed Algorithms for Topic Models",6a4b9d2eecc190f85a80adffe68ba52da77af94e,332885,0,0,38,1398650167,0
Paper,"Parallel Vector Field Embedding",e4a5f0b14499f2660ccfeb92ab3af65557fc2067,4100920,0,0,33,1398650167,0
Paper,"Multi-task Reinforcement Learning in Partially Observable Stochastic Environments",902bb50e342e15cafa431ff8c09f2df85b168c0f,670454,0,0,31,1398650167,0
Paper,"How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis",6588c6a4ac6f3af9467374146a433154c82a6ba1,1190557,0,0,40,1398650167,0
Paper,"Universal Kernel-Based Learning with Applications to Regular Languages(Special Topic on Mining and Learning with Graphs and Relations)",f7268a3b3b5c240236c163bda5d0bbcd6388a94a,282087,0,0,33,1398650167,0
Paper,"Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques",f620441db22049530cc97763ccc9bddd5769d61b,878323,0,0,56,1398650167,0
Paper,"Low-Rank Kernel Learning with Bregman Matrix Divergences",36fbeaf6bdd3f6743e3b9701d7dc4761275c4f96,390237,2,0,44,1398650167,0
Paper,"Learning Acyclic Probabilistic Circuits Using Test Paths",7791936dbe592270bf422723b26427053790de17,261886,0,0,28,1398650167,0
Paper,"Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning",214a7984eddbaf4f80683d2d3a25f7f937dfa209,377573,0,0,31,1398650167,0
Paper,"Learning Approximate Sequential Patterns for Classification",c0ddd60f3b29fb6c6dad16bfe87b2c4699d42c1b,199948,0,0,29,1398650167,0
Paper,"Combining Information Extraction Systems Using Voting and Stacked Generalization",7f914e88ed18d63b49f0cf8cf4878cb6d2b7b348,407661,0,0,41,1398650167,0
Paper,"Adaptive False Discovery Rate Control under Independence and Dependence",a6505f1745d9214d0fbc5bf66f7b790d8e8cc363,364223,0,0,28,1398650167,0
Paper,"Learning Linear Ranking Functions for Beam Search with Application to Planning",8c2e77b844696e7c0960ea4dd415192de1afc31e,354721,0,0,34,1398650167,0
Paper,"SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent",b34015056bd14ce7c9ef67cd8f4e209a8c7dc697,151450,0,0,26,1398650167,0
Paper,"Bayesian Network Structure Learning by Recursive Autonomy Identification",148196cd681145324b6e1ac5b92572ea388e1827,532303,0,0,37,1398650167,0
Paper,"Java-ML: A Machine Learning Library(Machine Learning Open Source Software Paper)",51f1fcb31e6a52e3ef2e30d60a9c7c03b82d8b3f,28916,0,0,149,1398650168,0
Paper,"Ultrahigh Dimensional Feature Selection: Beyond The Linear Model",58d5bf59fec3abe12ec451279938a4bc71ad6bfa,195894,0,0,26,1398650168,0
Paper,"MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures With Low Probability of False Positives During Use",19f00a21ce64d05278c5ecee12b6d0c1c2bd4b84,2044339,0,0,38,1398650168,0
Paper,"An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity",519e15dbeab4f1c9fb79c7699f75db6089c6b6bf,190689,0,0,31,1398650168,0
Paper,"Denoising Source Separation",510729a50981a497de66ac7cec570eb08a6b7c79,1950865,0,0,26,1398650168,0
Paper,"Expectation Consistent Approximate Inference",3c48b34e2cfd803c83257a6477ac0ab0ef49fa12,284259,0,0,30,1398650168,0
Paper,"Sparse Online Learning via Truncated Gradient",4dc4963adefc2e475287cf84eafe511d01a35d2b,287281,0,0,29,1398650168,0
Paper,"Working Set Selection Using Second Order Information for Training Support Vector Machines",8423422eb10dd6a9fbe8a6e1fdb6380913d6bd84,440141,0,0,30,1398650168,0
Paper,"Controlling the False Discovery Rate of the AssociationCausality Structure Learned with the PC Algorithm(Special Topic on Mining and Learning with Graphs and Relations)",c621ab96861aed981ed53a1bb39bdd86c6d95467,469197,0,0,28,1398650168,0
Paper,"Frames, Reproducing Kernels, Regularization and Learning",f33ce848cd9ff297cf94dee7a196b7b3a6141254,338347,0,0,27,1398650168,0
Paper,"Learning Multiple Tasks with Kernel Methods",6e30834fce44ef979e8c369ce942760284c550be,164094,2,0,50,1398650169,0
Paper,"Consistency and Localizability",c4d2545b047bdf64371c87bc26833b977c1fe8d8,223506,0,0,27,1398650169,0
Paper,"RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments(Machine Learning Open Source Software Paper)",c08bf14da29f4bf06dd18a4d530910390181e330,50879,0,0,32,1398650169,0
Paper,"Multiclass Boosting for Weak Classifiers",a92a8bf349ba69781681b3624b2653bdc5ec4398,194468,0,0,26,1398650169,0
Paper,"Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification",9e968a69072c4814b9e3bc4736619f0713d38c67,140389,0,0,24,1398650169,0
Paper,"When Is There a Representer Theorem? Vector Versus Matrix Regularizers",27b9e9808ffb19e126acc7ce1746d81fd81030f3,196765,0,0,30,1398650169,0
Paper,"Active Learning to Recognize Multiple Types of Plankton",7d532a9068cf1009a49d40ff7595b57703bbf08e,216981,0,0,37,1398650169,0
Paper,"Learning the Kernel with Hyperkernels (Kernel Machines Section)",4ab608c98f874ab10ec1b77af3b5ca83c85d2a51,434770,0,0,44,1398650169,0
Paper,"Using Local Dependencies within Batches to Improve Large Margin Classifiers",754104894f25f92ea726ac29a6e34d460bd61f5f,268976,0,0,33,1398650169,0
Paper,"Information Bottleneck for Gaussian Variables",d3cecd5b9df1147c2f62c43bcfb4f1d66f213a9f,518384,0,0,27,1398650169,0
Paper,"Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application",fd1725daad46d01243c91e36fa9226ef6f1e374c,274510,0,0,43,1398650169,0
Paper,"What's Strange About Recent Events (WSARE): An Algorithm for the Early Detection of Disease Outbreaks",5a52cfe03369a59117da5ee5c9660c1c8e1a19f1,276211,0,0,31,1398650169,0
Paper,"A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data",f4470eb8bc3a6f697df61bde319fd56e3a9d6733,401640,0,0,36,1398650169,0
Paper,"An MDP-Based Recommender System",c081d6f2e2177694c10aa6d77b0f569d718aa277,569219,0,0,59,1398650169,0
Paper,"Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods",821b0dafee4af63753f358d0e28ade1c0dbaba07,243920,0,0,28,1398650169,0
Paper,"Nonlinear Boosting Projections for Ensemble Construction",26f0ee842a3ac66f7e1a75d9585a06872284150b,10517989,0,0,39,1398650169,0
Paper,"Scalable Collaborative Filtering Approaches for Large Recommender Systems(Special Topic on Mining and Learning with Graphs and Relations)",c9a25c873abe71f40c1fc3719f476fe1d4386c76,335410,0,0,65,1398650169,0
Paper,"GPstuff: Bayesian Modeling with Gaussian Processes",5c019c7cab9d0872cb5bcdd8d0ce2e44e8c12ef6,74117,0,0,32,1398650169,0
Paper,"Beyond Fano's Inequality: Bounds on the Optimal F-Score, BER, and Cost-Sensitive Risk and Their Implications",3f4351f654434c014ffa7bd11b3bec535848fc15,542557,0,0,42,1398650169,0
Paper,"Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data",26490a33e07013d27b8cb1b0ff2cf6b899d82b5c,332072,0,0,26,1398650170,0
Paper,"Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets"",62e9371183b2b5d0df2bf79113fd91740d9dcbfd,131089,0,0,32,1398650170,0
Paper,"An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs",1ec2b027687067e295a2b1a03d611cf4d0c2f37e,827673,0,0,36,1398650170,0
Paper,"Gaussian Processes for Ordinal Regression",74e4922391a20e797c0e38949968f0329d7e396c,269257,0,0,29,1398650170,0
Paper,"Large Margin Methods for Structured and Interdependent Output Variables",993fe72cb0a9a730e0ae5ec863f4a346142399e2,240666,0,0,29,1398650170,0
Paper,"Stability of Randomized Learning Algorithms",18cf38dccb2548a5213233c1c11e3ae4438d4ca3,177757,0,0,37,1398650170,0
Paper,"Learning from Examples as an Inverse Problem",18d7de9c446474fba3abd5fa46f050d3616cc5e1,149249,0,0,36,1398650170,0
Paper,"A Unifying View of Sparse Approximate Gaussian Process Regression",963e38f4120b760c06855adc29cada57bc9c3086,254625,0,0,30,1398650170,0
Paper,"Classification with Gaussians and Convex Loss",fa6ea4ede21e0185c73f7f6e352c68fb6874a4a7,188003,0,0,28,1398650170,0
Paper,"Prioritization Methods for Accelerating MDP Solvers",513be53da526050b2f4fbcded68e6fe284c3fcec,542572,0,0,33,1398650170,0
Paper,"Classification in Networked Data: A Toolkit and a Univariate Case Study",c59e123ab69fe2b2002f3af9a2ba3c02963293ea,452337,0,0,34,1398650170,0
Paper,"Hash Kernels for Structured Data",faf29bb0ba94e087f1a8ad8dfdfe51a7f078e207,260296,2,0,38,1398650170,0
Paper,"On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning",30d522121723e2032764a9a2db95108fda7ed637,287253,0,0,25,1398650170,0
Paper,"Improving CUR Matrix Decomposition and the Nystrom Approximation via Adaptive Sampling",c9e45bd1ca311546e2695e614da5ba3f07b9c24f,691673,0,0,29,1398650170,0
Paper,"Multiclass Classification with Multi-Prototype Support Vector Machines",96dd2a85db288e33bd9369d0a5b255c0981ba22e,375435,0,0,24,1398650171,0
Paper,"Transfer Learning for Reinforcement Learning Domains: A Survey",062f6d7baad93e2bb253a751e4e13f5ee4310fbb,409391,0,0,37,1398650171,0
Paper,"Learning in Environments with Unknown Dynamics: Towards more Robust Concept Learners",03d75738d3c2a48e92843292acd94aebb60b6711,1111101,0,0,36,1398650171,0
Paper,"On the Nystrm Method for Approximating a Gram Matrix for Improved Kernel-Based Learning",b3e686c5b8f75085df7dde5f07d03bdcaa720264,174960,0,0,28,1398650171,0
Paper,"Nonextensive Information Theoretic Kernels on Measures",030a9f9b7403eb989205271685a12474c2ba5b26,377540,0,0,32,1398650171,0
Paper,"Learning Hidden Variable Networks: The Information Bottleneck Approach",f96a575be7a1439c66f0a5d5b06442275493f346,661619,0,0,31,1398650171,0
Paper,"Consistent Feature Selection for Pattern Recognition in Polynomial Time",d8c183b2d6c62e5ab43b980a9cec6be2827b5470,362456,0,0,31,1398650171,0
Paper,"Refinement of Reproducing Kernels",e754ca814cb6c74b06f4c3e409247f88d077aab4,239001,0,0,29,1398650171,0
Paper,"Assessing Approximate Inference for Binary Gaussian Process Classification",7c786a0cd4404f1266ef86e6a3523155755b0064,483692,0,0,33,1398650171,0
Paper,"Noise Tolerant Variants of the Perceptron Algorithm",15ce9dd60de4798bab0b6a20d538bf14d05bcf76,318935,0,0,36,1398650171,0
Paper,"Smooth -Insensitive Regression by Loss Symmetrization",f7a3961beba097d7af71accdb1da74a7eb64095e,416453,0,0,29,1398650171,0
Paper,"Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees",deffa88321d73009aa74fd5f5d958adf147e92cd,519895,0,0,31,1398650171,0
Paper,"Cautious Collective Classification",8a59a0bcd00c453594f7b284cf929bc1fbf63f5c,525676,0,0,34,1398650171,0
Paper,"Learning When Concepts Abound",f1e5b72c61f16a4944cb9093db694ae63bf9ce4b,351750,0,0,27,1398650172,0
Paper,"A Bayesian Model for Supervised Clustering with the Dirichlet Process Prior",450161730f8fe0c2950c446ea749e4c85c1b2538,227714,3,0,38,1398650172,0
Paper,"Learning Module Networks",238b93637b9599448ee54d04127f17099a8d573f,406702,0,0,63,1398650172,0
Paper,"Loop Corrections for Approximate Inference on Factor Graphs",b68dfac9d5f26fb7f89bc0915f5b162bc97a706a,781056,0,0,29,1398650172,0
Paper,"Penalized Model-Based Clustering with Application to Variable Selection",2e24eccfdef28d63b32ac448840980f79436776b,127934,0,0,33,1398650172,0
Paper,"Tree-Based Batch Mode Reinforcement Learning",b81244d60c7d9c0fb203ac3190e8d3582b8f37ba,1321891,0,0,31,1398650172,0
Paper,"Learning Halfspaces with Malicious Noise",0bb3abb4a388d52ef2c5b4f1fb86a7785ccce0c2,193753,0,0,38,1398650172,0
Paper,"Ranking the Best Instances",06fed548056eed0d17d12d817dd1e57284da2fe8,245836,0,0,31,1398650172,0
Paper,"Variational Message Passing",30ce6f474e843e7b65480679a86612b57c72d86c,456228,0,0,34,1398650172,0
Paper,"Managing Diversity in Regression Ensembles",b6457f6bfce562a8be2919e559d5c11c6acfb75c,251188,0,0,31,1398650172,0
Paper,"Efficient Online and Batch Learning Using Forward Backward Splitting",73f8e9a0eac100f8ab6409d510f50967c192af34,514500,0,0,32,1398650172,0
Paper,"Harnessing the Expertise of 70,000 Human Editors: Knowledge-Based Feature Generation for Text Categorization",077b92ed26aeecc050c4f268c066563c62e405ce,302310,0,0,41,1398650172,0
Paper,"Rearrangement Clustering: Pitfalls, Remedies, and Applications",5e336edd78c873fae1cf334f18fd531a3be8b039,866519,0,0,32,1398650172,0
Paper,"Generalization Bounds for Ranking Algorithms via Algorithmic Stability",aee818944bd83cd8d3ce374cb5bf9c44f1d21019,262740,0,0,48,1398650172,0
Paper,"Kernel Methods for Measuring Independence",931d10c8b632338ea2b30f6c749ff934ccf4c7a0,478952,0,0,29,1398650173,0
Paper,"Behavioral Shaping for Geometric Concepts",8acaba10076f9619a985ccc393b7b2c004ff9cb3,234071,0,0,35,1398650173,0
Paper,"Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes",cca65715cb31b53876c27c0f4ddcd2be9ad7036a,1343200,0,0,36,1398650173,0
Paper,"Undercomplete Blind Subspace Deconvolution",640ed853870355189e3727bbe0ae431844cf69c2,803707,0,0,32,1398650173,0
Paper,"Joint Harmonic Functions and Their Supervised Connections",baa7a77af59e0094b7e8cf7f8b63b712482b2a04,749025,0,0,29,1398650173,0
Paper,"A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation",283544b0bfa9937de05b7d11ea6de7798d85bf14,518047,0,0,35,1398650173,0
Paper,"A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians",add36f9231e0ff84311f823e9ff7149eff456fb2,192022,0,0,31,1398650173,0
Paper,"Universal Algorithms for Learning Theory Part I : Piecewise Constant Functions",7ff1031a0652dc89df2e421e96f5db3e329b295f,187308,0,0,36,1398650173,0
Paper,"The On-Line Shortest Path Problem Under Partial Monitoring",4bbf7327eb4fa9d8b3c5446ec672b47ca1ee7930,389686,0,0,32,1398650173,0
Paper,"Loopy Belief Propagation: Convergence and Effects of Message Errors",ee3ee33ffc7f2f65940e4f7f7071c3335eb70af2,354430,0,0,25,1398650173,0
Paper,"Change Point Problems in Linear Dynamical Systems",2b6280b26e86beb1b4f456224dea97ceed2fd78e,230780,3,0,47,1398650173,0
Paper,"Fast Kernel Classifiers with Online and Active Learning",e19fecddcaf73540fc5e63d10d36b964763ae0c2,507261,0,0,34,1398650173,0
Paper,"Convergence Theorems for Generalized Alternating Minimization Procedures",ad9358933c47d5b4862f97d9a0788346d3c92283,170834,0,0,35,1398650173,0
Paper,"Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification",17aad516d43bf716616f072927901baef114b835,478675,0,0,42,1398650173,0
Paper,"Learnability of Gaussians with Flexible Variances",324053932b051500ed6697786468f0a883adc498,226296,0,0,29,1398650173,0
Paper,"Algorithms and Hardness Results for Parallel Large Margin Learning",1c4b00397b095763f3dd14fb916b5dd391c485f6,222173,0,0,35,1398650173,0
Paper,"Regularization-Free Principal Curve Estimation",b506cdd629ea8c0c340cf02b46645a8ebc675ef8,1298327,0,0,27,1398650173,0
Paper,"Toward Attribute Efficient Learning of Decision Lists and Parities",2edbe151e1ba2a0c63b6c4367849e26cb2f6f21c,129715,0,0,28,1398650173,0
Paper,"Measuring Differentiability: Unmasking Pseudonymous Authors",ffd9193872a467ea32699c8493efb02ca0f40fdd,179223,0,0,28,1398650173,0
Paper,"Euclidean Embedding of Co-occurrence Data",5fcf3e50164ab453a28f487f7e8d5f44ddbe1103,908305,0,0,31,1398650173,0
Paper,"The Pyramid Match Kernel: Efficient Learning with Sets of Features",ac831f277885bb169067d73f660e092361daa8ec,7961938,0,0,35,1398650174,0
Paper,"Reproducing Kernel Banach Spaces for Machine Learning",d357547afa430de702b98cf13e85225b11c697d4,245376,0,0,26,1398650174,0
Paper,"Active Coevolutionary Learning of Deterministic Finite Automata",292679736beef01ce8ac8e6e69069d8cbeef2bf5,238246,0,0,38,1398650174,0
Paper,"Multi-class Protein Classification Using Adaptive Codes",a674b3f64e8c7cfd1949ba8e5f76726c6f0f5382,316488,0,0,33,1398650174,0
Paper,"Maximum Volume Clustering: A New Discriminative Clustering Approach",56b59a7aca9c896a2b318b965880702cba7ca4eb,531380,0,0,33,1398650174,0
Paper,"Minimax Regret Classifier for Imprecise Class Distributions",5d539a6f725c0f012fe158f786b1238d9e92a4a8,329705,0,0,34,1398650174,0
Paper,"Transfer Learning via Inter-Task Mappings for Temporal Difference Learning",1e77af32aaf43c32b30406d455c3ba4f85585024,511941,0,0,33,1398650174,0
Paper,"Relational Dependency Networks",a970d35f66fb5c847726dccbba20859157f0f6f3,2921412,0,0,30,1398650174,0
Paper,"Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach",8759bd084281cf78c6045dc3191e47666a6923bc,402625,0,0,34,1398650174,0
Paper,"Online Passive-Aggressive Algorithms",8203bc0f1ce7b42b06537d78b8b1315154813abb,372767,0,0,34,1398650174,0
Paper,"Sparse Boosting",c3cc042283428b9fce9114e881968a362fd71d56,242098,0,0,28,1398650175,0
Paper,"Consistency and Convergence Rates of One-Class SVMs and Related Algorithms",0490e9e2abbba7c1f79d8f9ce5e671ec08abe061,258632,0,0,33,1398650175,0
Paper,"Synergistic Face Detection and Pose Estimation with Energy-Based Models",78d2322a3b1b84e7de747110d9d271c918b32496,2242493,0,0,32,1398650175,0
Paper,"Improving the Reliability of Causal Discovery from Small Data Sets Using Argumentation(Special Topic on Causality)",d98191e0b45edf22fa510113fb6315156c371d16,325202,0,0,35,1398650175,0
Paper,"Covariate Shift Adaptation by Importance Weighted Cross Validation",633416b143a9e6ef89d9fb138179a72712a5bedf,273836,0,0,26,1398650175,0
Paper,"Fourier Theoretic Probabilistic Inference over Permutations",d9c86f4df1aa7b0173662a5a7d8058eca5942ca8,696975,0,0,22,1398650175,0
Paper,"Second Order Cone Programming Approaches for Handling Missing and Uncertain Data (Special Topic on Machine Learning and Optimization)",9135afd552fbbae3cffb883294da5b29bad5feb0,429291,0,0,39,1398650175,0
Paper,"Particle Swarm Model Selection(Special Topic on Model Selection)",c0d6ae7d64439abec77021312c7fa9fff0b7a063,563417,0,0,36,1398650175,0
Paper,"Streamwise Feature Selection",ffb340ed10e7cc97d2bb31a5ebc61d47216d02cf,163855,0,0,24,1398650175,0
Paper,"Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems",e55591692712e84ec086b796c930d5182b77c7bc,206079,0,0,28,1398650175,0
Paper,"Approximating the Permanent with Fractional Belief Propagation",2dace21ae42a298afec2e0a205257bf94b7a22d7,4157733,0,0,37,1398650175,0
Paper,"Learning the Structure of Linear Latent Variable Models",4e3120adac0a09818bca00485cc0e5511b9cdaca,451786,0,0,37,1398650175,0
Paper,"Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood",e4f58dc83c8dff5c08b8faac05907c971b4f9d25,1200268,0,0,30,1398650175,0
Paper,"Using Machine Learning to Guide Architecture Simulation",3405e560f80ca053f80116b7e3fef17583f2e846,809372,0,0,52,1398650175,0
Paper,"On the Complexity of Learning Lexicographic Strategies",892b58aa3a2bf66f9b96294f4f5124b9785d7243,203247,0,0,28,1398650175,0
Paper,"Combining PAC-Bayesian and Generic Chaining Bounds",a65b847b6fdd44bf84a6a7c5852c30251efcabe8,237118,0,0,33,1398650175,0
Paper,"Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems (Special Topic on Machine Learning and Optimization)",cd35083d3efcbc4eb0212f92831346b724f204d1,200296,0,0,135,1398650176,0
Paper,"Learning Factor Graphs in Polynomial Time and Sample Complexity",06e17519271a6492d76f0a59189a7ee7f5488a2c,355632,0,0,36,1398650176,0
Paper,"Point-Based Value Iteration for Continuous POMDPs",87ef9ab0ffb6ce89a2f2b4893fce0e822aea1ec3,527864,0,0,27,1398650176,0
Paper,"A Graphical Representation of Equivalence Classes of AMP Chain Graphs",39c2fdfdd24673eead933a415f84a238bbdb8273,308103,0,0,34,1398650176,0
Paper,"Segmental Hidden Markov Models with Random Effects for Waveform Modeling",590e4885c3053387cb96a1322d74adead690b025,529592,0,0,36,1398650176,0
Paper,"Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates",2323614427d18622693c0bc286ed28341735f35e,331367,0,0,30,1398650176,0
Paper,"Noisy-OR Component Analysis and its Application to Link Analysis",d07347babdc3166470e0d5a755d7533a5cf8adb0,529546,0,0,29,1398650176,0
Paper,"Online Learning of Multiple Tasks with a Shared Loss",ac5ee290188aea1123fc1316b8103da17d8c253a,259615,0,0,33,1398650176,0
Paper,"Maximum-Gain Working Set Selection for SVMs (Special Topic on Machine Learning and Optimization)",e0bd2a8edfc23f87a1076cfe42967ac99236947a,252094,0,0,28,1398650176,0
Paper,"Logistic Stick-Breaking Process",1b0d420bb3d183804b33d20aca0df7dd77c745c8,2248158,0,0,34,1398650176,0
Paper,"Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problems (Special Topic on Machine Learning and Optimization)",1fae6dbfbf47b107eb5aacd990d57c63431ad610,1037500,0,0,37,1398650176,0
Paper,"The arules R-Package Ecosystem: Analyzing Interesting Patterns from Large Transaction Data Sets",7e5c3ac40b1b0bea28dcaa6cb5e9c05e5b3a68ef,165055,0,0,32,1398650177,0
Paper,"Proximal Methods for Hierarchical Sparse Coding",d0d17069650e8d58979b4a2230c9c4ceab89323d,611345,0,0,27,1398650177,0
Paper,"A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin",9df16aa64cc9fd65e8b97b8c49824c021dfd18fd,244701,0,0,33,1398650177,0
Paper,"Concave Learners for Rankboost",c27abdf703fdc5f4ae00779f3cd94aaa1a9fabf9,170755,0,0,30,1398650177,0
Paper,"Unsupervised Similarity-Based Risk Stratification for Cardiovascular Events Using Long-Term Time-Series Data",645268cc6d67bed015329f662a1fe0728cb50fcb,276065,0,0,33,1398650177,0
Paper,"In Search of Non-Gaussian Components of a High-Dimensional Distribution",10a165ce9747da34cb29632b9a5cce7912fd8ddc,1276281,0,0,48,1398650177,0
Paper,"Asymptotics in Empirical Risk Minimization",b8cfa79adb8e35287c9ace14cecceb964cb808b0,150529,0,0,32,1398650177,0
Paper,"Neyman-Pearson Classification, Convexity and Stochastic Constraints",c155687e5522ae11e5ec2d018a96e0c27a8d9acc,187159,0,0,26,1398650177,0
Paper,"Generalized TD Learning",7f095755a42c38cd1dfa2f08bcd8a6371249cc5e,400392,0,0,33,1398650177,0
Paper,"Walk-Sums and Belief Propagation in Gaussian Graphical Models",0f7ad02c15111c41922fc6f445fda383f760ce09,345369,0,0,33,1398650177,0
Paper,"Building Support Vector Machines with Reduced Classifier Complexity (Special Topic on Machine Learning and Optimization)",f91fa40ea6d17f2fa2b020ff21838ae5a8fef79b,244174,0,0,47,1398650177,0
Paper,"QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines",2aa615cad7ebba3dab42edf5f6a62fb805fcf28d,322124,0,0,34,1398650177,0
Paper,""Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks",2ad4d685df8fdcd5f6b735fd3a0e8295f0501b47,663195,0,0,37,1398650177,0
Paper,"Inverse Reinforcement Learning in Partially Observable Environments",3b46631410d926a0424de8036eadedd16773e1a5,626031,0,0,41,1398650178,0
Paper,"Building Blocks for Variational Bayesian Learning of Latent Variable Models",b1637b1db97ed934c05b61b6aed29743647cb76c,426827,0,0,36,1398650178,0
Paper,"Hierarchical Average Reward Reinforcement Learning",a15142ab25e34c2e5b3af80186f528305070880a,332685,0,0,28,1398650178,0
Paper,"Large Margin Hierarchical Classification with Mutually Exclusive Class Membership",c81e1a1ae19abcf4bbb3a51fe6134778fd0d1985,269391,0,0,27,1398650178,0
Paper,"Causal Graph Based Decomposition of Factored MDPs",386834e90cfa8d286a02e1aea2009b56f6a01ff0,305908,0,0,37,1398650178,0
Paper,"MSVMpack: A Multi-Class Support Vector Machine Package",33ae95873171c2644aebd2858ef7da5c792c9262,46009,0,0,31,1398650178,0
Paper,"Training SVMs Without Offset",ae48285c025e30986bbe68e197863f4857690b5b,922835,0,0,29,1398650178,0
Paper,"Bounded Kernel-Based Online Learning",2aa2212325162e2d22c8fbb2790fb1b5d30fe275,429447,0,0,40,1398650178,0
Paper,"Learning Parts-Based Representations of Data",0357c6b615807429d48a6e0d661a77fbef1ad122,440259,0,0,34,1398650178,0
Paper,"Semi-Supervised Learning with Measure Propagation",7400e484c2bdc03641f6e277f868abee8f37f56f,971519,0,0,30,1398650178,0
Paper,"Convex and Network Flow Optimization for Structured Sparsity",3c3a188d4c891f1dc8aa40ef2140e88b63efe684,763932,0,0,39,1398650178,0
Paper,"LPmade: Link Prediction Made Easy",8b1578efd4408a6f87ee11704b6b0077763cab40,49331,0,0,31,1398650178,0
Paper,"Truncating the Loop Series Expansion for Belief Propagation",8a7a6032b5ba4accb6e64faf9a6d368df80654db,1310581,0,0,30,1398650178,0
Paper,"A Hierarchy of Support Vector Machines for Pattern Detection",fdc712a3fbac1b24a3abbe391f720fcf68409a7b,1653637,0,0,36,1398650178,0
Paper,"Generalized Bradley-Terry Models and Multi-Class Probability Estimates",19815316b7b4aa16f6abf2bc563a05b995903c22,402410,0,0,28,1398650179,0
Paper,"Integrating Nave Bayes and FOIL",8f7ffe6997860f719aed271668c1e1fdc0888647,223183,0,0,30,1398650179,0
Paper,"Producing Power-Law Distributions and Damping Word Frequencies with Two-Stage Language Models",f5c1883a0bbd33e97e7faa573d2acaf2eb34df6e,560663,0,0,34,1398650179,0
Paper,"MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals",bb33c60ea59f55679d51c8070c51206265b93b09,395928,0,0,34,1398650179,0
Paper,"Computationally Efficient Convolved Multiple Output Gaussian Processes",8229e8964303fb5bb9e62ed070b79d1e2198a945,646802,0,0,32,1398650179,0
Paper,"Polynomial Identification in the Limit of Substitutable Context-free Languages",8582796ce77f239d88f9d65e026c7bf64f7ce642,150260,0,0,27,1398650179,0
Paper,"Locally Defined Principal Curves and Surfaces",ca245e9710f3d0d8205c714dc2380642e0f1c879,2874882,0,0,28,1398650179,0
Paper,"Laplacian Support Vector Machines Trained in the Primal",ca13f9759a4a9c77cb3eac5d644bd6e63976369f,502275,0,0,38,1398650179,0
Paper,"Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach (Special Topic on Inductive Programming)",9892859c9259965676386476680f11f1f59976de,258888,0,0,32,1398650179,0
Paper,"Introduction to Special Issue on Machine Learning Approaches to Shallow Parsing",62e4b0e2c43b84917900a16ba787a0bfe39d1101,392170,0,0,44,1398650179,0
Paper,"Kernel-Based Learning of Hierarchical Multilabel Classification Models (Special Topic on Machine Learning and Optimization)",94712fb735291e85dc0ba56754845a08d5fff917,193087,0,0,34,1398650179,0
Paper,"Stability Properties of Empirical Risk Minimization over Donsker Classes",164dfc2054da248f85722945ffb0777ddc89eddc,164348,0,0,32,1398650179,0
Paper,"Local Discriminant Wavelet Packet Coordinates for Face Recognition",1ebde5e7722bd9e993343df65704cf777d08f173,371959,0,0,43,1398650180,0
Paper,"Learning Transformation Models for Ranking and Survival Analysis",d426f5586e5b5b79155a093659a49e45df66d736,806046,0,0,33,1398650180,0
Paper,"Structured Prediction, Dual Extragradient and Bregman Projections (Special Topic on Machine Learning and Optimization)",161c197fd72aeb5eb6f06162174759bafacb6463,534290,0,0,40,1398650180,0
Paper,"Large Margin Semi-supervised Learning",d9e261b11c763abf68d852e6b6b824a7cca7b6de,260985,0,0,24,1398650180,0
Paper,"Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm",9938d5a4bcf4e7986b1059cdb293a5beb65d6233,199047,0,0,29,1398650180,0
Paper,"Domain Decomposition Approach for Fast Gaussian Process Regression of Large Spatial Data Sets",59b1b88dedf188188da1681cc913c18ca9c97bec,427930,0,0,34,1398650180,0
Paper,"Learning from Partial Labels",09cf3400cedcc98b277bb073780faa79a0b80474,1913469,0,0,37,1398650180,0
Paper,"Efficient Structure Learning of Bayesian Networks using Constraints",b5d0a272f00e853c185784d22b3cb5f4c604b153,215951,0,0,33,1398650180,0
Paper,"Generalization Bounds for the Area Under the ROC Curve",325a17176cefb598e7776562e69ef3dfc1fd2480,259604,0,0,33,1398650180,0
Paper,"Variational Inference in Nonconjugate Models",de0d3b62fd9c1efd79ddf106dfe1036d602fa012,500052,0,0,24,1398650181,0
Paper,"Efficient Learning of Label Ranking by Soft Projections onto Polyhedra (Special Topic on Machine Learning and Optimization)",edbb2295a1ce9b8d0a55255c4ea01965b0be4e99,572889,0,0,26,1398650181,0
Paper,"A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs",965bb1f04693a15ad715ed355c6d910bbb81a4dc,157284,0,0,34,1398650181,0
Paper,"On the Representer Theorem and Equivalent Degrees of Freedom of SVR",a69d1eef1b59b1fe305e6951d80a6ef27608ef25,463086,0,0,27,1398650181,0
Paper,"Multiple Kernel Learning Algorithms",83f0dc25b1c9175df96fbe168bd153226b4fa473,395805,0,0,28,1398650181,0
Paper,"Multi-Task Learning for Classification with Dirichlet Process Priors",38cf8e6441722f7ca42d2c2c28fe8248e2f55472,250967,0,0,26,1398650181,0
Paper,"Efficient Learning with Partially Observed Attributes",04722103ad77ab5639f019773a828c82183f8f60,187318,0,0,31,1398650181,0
Paper,"Graph-Based Hierarchical Conceptual Clustering",a874a2fe203f2cce8fb34e3a2cc16b7f6b25fd32,207105,0,0,33,1398650181,0
Paper,"The Learning-Curve Sampling Method Applied to Model-Based Clustering",4438c8dba4c0e08576a6cbe1db3ef9ab04c9f922,193580,0,0,29,1398650181,0
Paper,"Collaborative Multiagent Reinforcement Learning by Payoff Propagation",592208652eb5156681acc26f10c6521526830884,521268,0,0,36,1398650181,0
Paper,"Adaptive Online Prediction by Following the Perturbed Leader",18f0cf1d83c83b51db477e84fd770d5ac05dbee6,191610,0,0,31,1398650181,0
Paper,"The Indian Buffet Process: An Introduction and Review",4590e35ca648f463521828322f1d12393677505e,407748,0,0,92,1398650181,0
Paper,"Learning a Robust Relevance Model for Search Using Kernel Methods",63c867e896288648b97055456a9bad2c6527c35d,256735,0,0,29,1398650181,0
Paper,"Learning Permutations with Exponential Weights",371e6a8a2f445e8017eac1f9c94cdc7b60be0524,246967,0,0,27,1398650181,0
Paper,"Natural Language Processing (Almost) from Scratch",824fd119b03225610249c0ce6ceae778dcb7e28d,424780,2,0,210,1398650182,0
Paper,"Information, Divergence and Risk for Binary Experiments",d905fed7d452becae1f8d4500845f53475ceb50e,1505604,0,0,36,1398650182,0
Paper,"Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions",500f721722fc56105b977d78a9dbda71e6b95480,303531,0,0,30,1398650182,0
Paper,"A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization",30cff6756b819112cf94ba44f6f99d527f5a6bb7,242084,0,0,35,1398650182,0
Paper,"Inner Product Spaces for Bayesian Networks",b328509aa436f2928fd95411b75892fa76c154b7,164607,0,0,27,1398650182,0
Paper,"Non-Parametric Estimation of Topic Hierarchies from Texts with Hierarchical Dirichlet Processes",f0d7c8957eb8166c781afcb9d4cb800f88dc8d1c,524924,0,0,27,1398650182,0
Paper,"Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies",044f66e5f830e8af633c12126e17b83e7ca11159,389203,0,0,49,1398650182,0
Paper,"Efficient Computation of Gapped Substring Kernels on Large Alphabets",dff9129acc8eb68901209bc0e4403440780f2f52,254613,0,0,26,1398650182,0
Paper,"Uniform Object Generation for Optimizing One-class Classifiers (Kernel Machines Section)",a789d64967f290658051009c71ac12ce521f53f8,188011,0,0,29,1398650182,0
Paper,"Approximate Marginals in Latent Gaussian Models",46b85abadd8047e372ad9d828267c3caf2010015,3570298,0,0,31,1398650182,0
Paper,"Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection",45c959bd128b0d7c8f8bb56a142feace3ded16aa,243076,0,0,29,1398650182,0
Paper,"Distance Dependent Chinese Restaurant Processes",e8ab6453351bea02ae0ba4ff3f6749bd4734a203,1964718,0,0,29,1398650183,0
Paper,"Exploring Strategies for Training Deep Neural Networks",d712b334f78b0dc31820f9faaf9f3c59c70799b9,973024,0,0,127,1398650183,0
Paper,"Ensemble Pruning Via Semi-definite Programming (Special Topic on Machine Learning and Optimization)",dd46e5dd71f1d030fecbeaefe8f160db8a667c4c,262394,0,0,30,1398650183,0
Paper,"Analysis of Variance of Cross-Validation Estimators of the Generalization Error",822c908e2655cccc42ffe1cdbdc3b79454294032,294942,0,0,27,1398650183,0
Paper,"Parameter Screening and Optimisation for ILP using Designed Experiments",7ee4af34fd1bdd06a40e4a8d7d946f399c919444,281421,0,0,30,1398650183,0
Paper,"Exploiting Best-Match Equations for Efficient Reinforcement Learning",70c84121a79df3e988df8f214c107352a7a04808,495827,0,0,34,1398650183,0
Paper,"Learning Latent Tree Graphical Models",230f679124442f5ce05668b6ebf8a8f9f27337df,734638,0,0,30,1398650183,0
Paper,"Kernel Regression in the Presence of Correlated Errors",5a2e5d42009b860ea5c3967332603f4f5aca49ea,465077,0,0,38,1398650183,0
Paper,"Learning with Decision Lists of Data-Dependent Features",bad76c32d58770622c34f7b34cfb61aaa72b7626,196481,0,0,27,1398650183,0
Paper,"Incremental Support Vector Learning: Analysis, Implementation and Applications (Special Topic on Machine Learning and Optimization)",c10a3083a19620e20dd28eec55d39763695469c2,259910,0,0,37,1398650183,0
Paper,"Improved Moves for Truncated Convex Models",9d1759049019d25a6c9cb965116e102a9692698b,526599,0,0,27,1398650183,0
Paper,"Marginal Likelihood Integrals for Mixtures of Independence Models",60f075fed1a4fd3d039561039957fa80bdead00c,177752,0,0,27,1398650183,0
Paper,"Online Learning with Samples Drawn from Non-identical Distributions",bf4dff3c524cb89cad4cefa7d237abbf0278493e,210126,0,0,23,1398650183,0
Paper,"A Generalized Kernel Approach to Dissimilarity-based Classification (Kernel Machines Section)",620871753fb3a80f0177dcc20a193648dbb8197d,451295,0,0,29,1398650184,0
Paper,"Worst-Case Analysis of Selective Sampling for Linear Classification",6337ffb8648d6c0dd01b9d5463f86c66f7b1c96f,184339,0,0,27,1398650184,0
Paper,"Unsupervised Supervised Learning II: Margin-Based Classification Without Labels",abfba3928f07f06af6d2f37f98c56731144689dd,253973,0,0,31,1398650184,0
Paper,"A Classification Framework for Anomaly Detection",95df4fceb716fe136e921db7821686a6f1665020,181540,0,0,44,1398650184,0
Paper,"Learning to Classify Ordinal Data: The Data Replication Method",8381325b62839851a03b66edfa8fc395a6c73abd,448241,1,0,37,1398650184,0
Paper,"MULAN: A Java Library for Multi-Label Learning",06e59f0717ac2e28a288ec03601d0de30f8bb28f,29581,0,0,51,1398650184,0
Paper,"Information Rates of Nonparametric Gaussian Process Methods",73fdec12ac6011e192ec55f460dfba81a166d40e,198200,0,0,29,1398650184,0
Paper,"Stochastic Methods for l1-regularized Loss Minimization",4643cebc79b7e7f77ca33093c614cb171a4dac9c,517561,0,0,29,1398650184,0
Paper,"Experiment Selection for Causal Discovery",695290318fd1fc5633f883f832bc089bdf840538,1266907,0,0,25,1398650184,0
Paper,"Linear Programming Relaxations and Belief Propagation -- An Empirical Study (Special Topic on Machine Learning and Optimization)",adc57fd2617de4ac0da9741eb465bab36f80d757,802836,0,0,51,1398650184,0
Paper,"On Model Selection Consistency of Lasso",9ca348a1e9b6a56f90e53ab1cedf7ab783f55eb6,172939,0,0,29,1398650184,0
Paper,"Spam Filtering Using Statistical Data Compression Models (Special Topic on Machine Learning for Computer Security)",cfb1b3100fcf1175e88124ae04b49533cdff2c87,336310,5,0,59,1398650184,0
Paper,"Differentially Private Empirical Risk Minimization",e81f29f96c44213cb50e33cf457d621a4a298a26,339061,0,0,27,1398650184,0
Paper,"Efficient Program Synthesis Using Constraint Satisfaction in Inductive Logic Programming",d65a9e6281772cd06869014308ca69018f45e2f5,278958,0,0,34,1398650185,0
Paper,"Discriminative Learning Under Covariate Shift",88f059942483326a34a7990450d440bba733ae4e,165700,0,0,27,1398650185,0
Paper,"A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes",55f4ffc91509ab0f716cb86c642585a25bfb93cd,372874,0,0,43,1398650185,0
Paper,"In All Likelihood, Deep Belief Is Not Enough",9f5e775d7ce6272037c3bd72df4390c493acfa7b,447320,0,0,49,1398650185,0
Paper,"Infinite- Limits For Tikhonov Regularization",d9af67a76d835084cfec13a08989536613c5b34e,223738,0,0,27,1398650185,0
Paper,"Learning a Mahalanobis Metric from Equivalence Constraints",0a1cf731c65a7252487bf400a035eee85da7319a,868954,0,0,44,1398650185,0
Paper,"Text Chunking based on a Generalization of Winnow",1fe06c45173b62ff473cc3da044ec688e8c862a0,199638,0,0,39,1398650185,0
Paper,"Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data",2cc1158f0537514d2050c24d07a09ac9bebfd3da,259925,0,0,37,1398650185,0
Paper,"JKernelMachines: A Simple Framework for Kernel Machines",525232019cb30357948aee5a5d0132c5788a739c,69750,0,0,27,1398650185,0
Paper,"NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM",a0c95108809d820da29be0b47242fcd7823d952e,452726,0,0,28,1398650185,0
Paper,"Support Vector Machine Active Learning with Applications to Text Classification",639b6fa478c23316be69c49ea4e42dfc3d73371d,309683,0,0,99,1398650185,0
Paper,"On Using Extended Statistical Queries to Avoid Membership Queries",b0ba3a0e719c2b3ee91c38662dc0909c6786ab9b,1478487,0,0,27,1398650185,0
Paper,"Robust Approximate Bilinear Programming for Value Function Approximation",453d9ce6d3a6f23b5909fbefbbab84b0c74bb855,262335,0,0,31,1398650185,0
Paper,"Nonlinear Models Using Dirichlet Process Mixtures",077943f332927f73167acaf86c83073fcdbb0f69,231280,0,0,38,1398650186,0
Paper,"Introduction to the Special Topic on Grammar Induction, Representation of Language and Language Learning",71e1c9692c556e252aa7e2f4715c419ee447039b,25980,0,0,75,1398650186,0
Paper,"Learning Horn Expressions with LOGAN-H",f4e3b96b5b9e4e4974f218341b30f4d7f59afa8c,814712,0,0,30,1398650186,0
Paper,"Posterior Sparsity in Unsupervised Dependency Parsing",f933c7d421ba53868b3a03bd73728294abdb70d5,383819,0,0,30,1398650186,0
Paper,"lp-Norm Multiple Kernel Learning",29c6ca8dd86b10b4d0870f86dac6e78eebe268a1,434395,0,0,31,1398650186,0
Paper,"Step Size Adaptation in Reproducing Kernel Hilbert Space",5640eae7ca2e270385c383c9c2e1b7969d95c246,450312,0,0,56,1398650186,0
Paper,"Anechoic Blind Source Separation Using Wigner Marginals",3f009f0f96c7fc816eaff965df80a2d33d8237c9,773750,0,0,44,1398650186,0
Paper,"Distance Metric Learning for Large Margin Nearest Neighbor Classification",530e4635cf63a20a58a2e032707730ca226a61f0,1980873,0,0,54,1398650186,0
Paper,"Sparse Linear Identifiable Multivariate Modeling",d2a6b778455b4284bfe0a44ea794ce35cf4573f4,533988,0,0,40,1398650187,0
Paper,"Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization",ba016e245fb44ec204437338eecd1cf4b94c65a8,711510,0,0,27,1398650187,0
Paper,"Double Updating Online Learning",0bc529b79f14c92c8a4b273b3197601aafb4c5d0,302619,0,0,38,1398650187,0
Paper,"Learning Nondeterministic Classifiers",5d1dbaf04b0e5b1b254f4167267f3b345a8e6d7e,422558,0,0,38,1398650187,0
Paper,"Stagewise Lasso",defc2d193d959e9819bddb6d9ca11eaa70802569,611527,0,0,25,1398650187,0
Paper,"Scikit-learn: Machine Learning in Python",5ba4939a00a9b21629a0ad7d376898b768d997a3,42310,21,0,2302,1398650187,0
Paper,"Parallel Algorithm for Learning Optimal Bayesian Network Structure",cc032abd599138c3215423c5a746c4f24b70714c,394237,0,0,37,1398650187,0
Paper,"Learning Multi-modal Similarity",34ca78c54a4f49615dd060a9d31fffaf4646ba89,468434,0,0,32,1398650187,0
Paper,"Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood",43174c736752d532c6beef2db3a51f160f3e20d4,447140,0,0,34,1398650187,0
Paper,"CARP: Software for Fishing Out Good Clustering Algorithms",5e484b1c2b27bcb2666f500789826af07d052fe5,584436,0,0,36,1398650187,0
Paper,"Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression",edf90fe1660c45f75c07a34842d2c6b2361e13e7,817863,0,0,32,1398650187,0
Paper,"Learning Minimum Volume Sets",c672b8774ca121ea3393cdbc25be2d99d17cf79f,917285,0,0,30,1398650187,0
Paper,"Value Regularization and Fenchel Duality",465d5a852f238ee8a686c9cbaab84f447477c45d,299190,0,0,28,1398650187,0
Paper,"On the Learnability of Shuffle Ideals",1994966b15a813e041fd3b12333cbb91fd51ee86,181534,0,0,32,1398650187,0
Paper,"Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples",f3a3b1a97bd8fdb762685f05318b822e295fa059,416149,0,0,30,1398650188,0
Paper,"Large Scale Transductive SVMs",fe5196636bb4f1f391220fbe64d73393c8ef1481,220629,0,0,28,1398650188,0
Paper,"Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis",34e81945b75f04fc9d761ff03107482eb6fdbda6,487931,0,0,28,1398650188,0
Paper,"Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Functions on Graphs",a14356df526b633b5280cecf9f65e4b6141b609c,2025724,0,0,49,1398650188,0
Paper,"Structured Variable Selection with Sparsity-Inducing Norms",a9da48e21b8fb1dbf8f7736d5f04a4e688c9b3f7,446849,0,0,29,1398650188,0
Paper,"Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining",2cf0863d0ecaeffdf82e75ae8b572cc0da2ee4f6,278964,0,0,34,1398650188,0
Paper,"Learning a Hidden Hypergraph",0072e334eb0341d1a3aa1228d16142da5da7729a,178935,0,0,42,1398650188,0
Paper,"Learning with Structured Sparsity",47a3b370d978d2db44d8d4b16198910f8008eece,518696,0,0,33,1398650188,0
Paper,"A Family of Simple Non-Parametric Kernel Learning Algorithms",25e2c246cb979b5177f6f503e7b9936e6502e9e2,620863,0,0,43,1398650188,0
Paper,"On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines (Kernel Machines Section)",e5e4db66ae2b6757f9a4ddca5ea6793db4c9b267,494387,0,1,29,1398650188,0
Paper,"X-Armed Bandits",82a415bed4fd188b34ea7b50c2b92c5659428a50,835486,0,0,31,1398650188,0
Paper,"Dynamics and Generalization Ability of LVQ Algorithms",d70bf26ff67cac69225ba1aad75beb599dcb47bb,608475,0,0,33,1398650188,0
Paper,"Dirichlet Process Mixtures of Generalized Linear Models",3661cf7a069b9defb6cf5dd385e4ba5c03c43052,2926718,0,0,31,1398650188,0
Paper,"Learning Equivariant Functions with Matrix Valued Kernels",46a545c2336e13e237de06acbc584afd7a1cded7,495753,0,0,33,1398650189,0
Paper,"Margin Trees for High-dimensional Classification",26038553c5011297c6784264b8895edc840a130a,102520,0,0,31,1398650189,0
Paper,"Bayesian Quadratic Discriminant Analysis",1a41a2ea96101eef06364ea8dc31cfff7ee6abef,196901,0,0,30,1398650189,0
Paper,"The Interplay of Optimization and Machine Learning Research (Special Topic on Machine Learning and Optimization)",f59218767a5dade9760abec4d64dd1ef71bc7581,118184,0,0,41,1398650189,0
Paper,"Bayesian Generalized Kernel Mixed Models",5aa43bec0cb3510349f9314a9cf9f7a57fa9678f,340760,0,0,35,1398650189,0
Paper,"Minimum Description Length Penalization for Group and Multi-Task Sparse Learning",95477d6818dba2c532684af7bd9a6d645b0c14d5,317951,0,0,33,1398650189,0
Paper,"Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling",ee546a96c061eeaaac4aadb9f94cae166ad892b8,432510,0,0,30,1398650189,0
Paper,"Universality, Characteristic Kernels and RKHS Embedding of Measures",517b5ac8eca29f7553968a5a93f8e500f8f6243b,369711,0,0,28,1398650189,0
Paper,"An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression",2deb1384378d8b6b777db438b4f57ff7866274a5,910983,0,0,41,1398650189,0
Paper,"Refinable Kernels",27a1cc2a72cf88a10772e3e7ff8d03c3e4bb4a0d,261780,0,0,30,1398650189,0
Paper,"Linear Programs for Hypotheses Selection in Probabilistic Inference Models (Special Topic on Machine Learning and Optimization)",981132f46a26b773c8c1a9396372ce6546861867,127427,0,0,30,1398650189,0
Paper,"Core Vector Machines: Fast SVM Training on Very Large Data Sets",5f89897c06b7151321830600009ef153f6b45941,417311,0,0,51,1398650189,0
Paper,"A Linear Non-Gaussian Acyclic Model for Causal Discovery",83c385e427011f7e57c43b389adb63247ac98490,417284,0,0,34,1398650189,0
Paper,"Group Lasso Estimation of High-dimensional Covariance Matrices",b94b1d2d051795e089f6a3e99ae13f77ec7d2719,354443,0,0,27,1398650190,0
Paper,"A Simulation-Based Algorithm for Ergodic Control of Markov Chains Conditioned on Rare Events",e40d76248365e1e8d49d052f1b0c2eb3aa3d7a6e,219604,0,0,38,1398650190,0
Paper,"Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections",b6a11a170af5a00d6a1ccb210305a0d1cec566f2,337826,0,0,31,1398650190,0
Paper,"Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters (Special Topic on Model Selection)",08b92c86b378c859ff1a1cae59db757f3ac28f9f,153711,0,0,34,1398650190,0
Paper,"Separating Models of Learning from Correlated and Uncorrelated Data (Special Topic on the Conference on Learning Theory 2005)",b591e6306d970a3db3a2d7217a4d2ddf38516707,132695,0,0,33,1398650190,0
Paper,"Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation",7bcab37cc9727bef5eac69a8b43826f99d7493c2,852468,0,0,39,1398650191,0
Paper,"Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation",0fc69cb913852ee93543f0fe741755e03ba081b4,266307,0,0,33,1398650191,0
Paper,"Efficient SVM Training Using Low-Rank Kernel Representations (Kernel Machines Section)",f7e3faa34b142adb79f3c869e33a7cbc2fc3cc19,463052,0,0,29,1398650191,0
Paper,"Hyper-Sparse Optimal Aggregation",9fdf62245fad8cc91904e1d6db646b3cd2af6b8e,900657,0,0,36,1398650191,0
Paper,"DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model",65bc332a9ff22064b7d377174051e15955826649,934533,0,0,36,1398650191,0
Paper,"Anytime Learning of Decision Trees",3f8d53cdaca8ec8852963bef9f37d60d7309860e,364505,3,0,38,1398650191,0
Paper,"New Algorithms for Efficient High-Dimensional Nonparametric Classification",1311aa4cb92a3da7928a5dea4c43de7a6840bb0d,183679,0,0,40,1398650191,0
Paper,"Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting (Special Topic on Inductive Programming)",d69b2a90865890327ccb1386080218970d16e5d4,552761,0,0,40,1398650191,0
Paper,"PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers",48770b460f934ebe6ccc2a05d9e913fa62ccd5a8,225562,0,0,26,1398650191,0
Paper,"Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results",8e34e6991e7bb8c97b82ab309623e5602a8f0610,146637,0,0,33,1398650191,0
Paper,"Dimension Reduction in Text Classification with Support Vector Machines",2b73ffdc6583445eb35d6555d487444f15fb789d,107393,0,0,35,1398650191,0
Paper,"Evolutionary Function Approximation for Reinforcement Learning",a7bc5f6bc983877b6fdfa38167d15440e321b9f2,1552620,0,0,32,1398650191,0
Paper,"Active Learning with Feedback on Features and Instances",0e91d239c92daf6cefe25e8314fa13e48baa1105,386122,0,0,39,1398650191,0
Paper,"Theoretical Analysis of Bayesian Matrix Factorization",15fe36f7944a8d40c7e3dbdb9c3cb2c94ffabdc2,581483,0,0,39,1398650191,0
Paper,"Large Scale Multiple Kernel Learning (Special Topic on Machine Learning and Optimization)",eb2f99fb247f0f374e63f0efd4a6874466658f31,937229,0,0,39,1398650191,0
Paper,"Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation",1376e352dc93e1e2066c34531e9f5f39ad442bca,1449207,0,0,45,1398650191,0
Paper,"General Polynomial Time Decomposition Algorithms (Special Topic on the Conference on Learning Theory 2005)",85cad139e5d7933d2a0a9609042d7f65d5234910,154044,0,0,39,1398650192,0
Paper,"Introduction to the Special Issue on Kernel Methods (Kernel Machines Section)",d16ac871220cb7c33415ffaa77bdd94309cb7b3c,81052,0,0,32,1398650192,0
Paper,"A Bayesian Approximation Method for Online Ranking",61f3fcb50a5e10fd40d461042e9bc2d33e263e9f,236160,0,0,45,1398650192,0
Paper,"SparseRobust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory",4f11055a66aee0bc992534acd0a0bfad33a284d0,507877,0,0,33,1398650192,0
Paper,"Bayesian Network Learning with Parameter Constraints (Special Topic on Machine Learning and Optimization)",56d216a606fa1fcf0e1338b7f6252889e7ec351a,259545,0,0,45,1398650192,0
Paper,"Robust Gaussian Process Regression with a Student-t Likelihood",e49fb903a9419d945066f323bd1a6785eeb8f55c,759216,0,0,32,1398650192,0
Paper,"Shallow Parsing using Specialized HMMs",2d7636b11b729d5c096b0195125f45d396d17314,308350,0,0,33,1398650192,0
Paper,"Handling Missing Values when Applying Classification Models",2c4f83e3f6f4e0468ac16780caedd93c5799e263,389647,0,0,34,1398650192,0
Paper,"Forest Density Estimation",1d44d4af516810eca11fdeb7430b1cafc6971c59,809726,0,0,41,1398650192,0
Paper,"New Horn Revision Algorithms",38e420740a5236e66eda4757734adb1380289565,149384,0,0,31,1398650192,0
Paper,"On Inferring Application Protocol Behaviors in Encrypted Network Traffic (Special Topic on Machine Learning for Computer Security)",fd60073fa47e2fe363b49d64545720cac67f2797,275123,3,0,67,1398650192,0
Paper,"Estimation of Gradients and Coordinate Covariation in Classification",aca9aaca4f8f1084ea4f140ffdb2f1c44b05bcdc,317438,0,0,35,1398650192,0
Paper,"From External to Internal Regret (Special Topic on the Conference on Learning Theory 2005)",9682919797e53ce79c185a851587e5a575574dff,163168,0,0,29,1398650192,0
Paper,"Estimating Functions for Blind Separation When Sources Have Variance Dependencies",00fcc670016f036c2ff9f3df3c0d3437356e0588,658280,0,0,41,1398650193,0
Paper,"Evolutionary Model Type Selection for Global Surrogate Modeling",2dc016a42d36912d559e9896404a8afd43ccf47e,1277094,0,0,40,1398650193,0
Paper,"A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis",2b2586a299e191fa8329d6ca35f1892d174071f4,399654,0,0,65,1398650193,0
Paper,"A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With p Larger Than n",c782c5a3a2161449b7b4c7aa9cb57dab69887027,685163,0,0,30,1398650193,0
Paper,"Incorporating Functional Knowledge in Neural Networks",f52efac637894c976728119495b979790e2b894e,181142,0,0,44,1398650193,0
Paper,"Learning to Detect and Classify Malicious Executables in the Wild (Special Topic on Machine Learning for Computer Security)",ab04cea5def5dc64eb39a5ace8f958aeff955c13,206729,4,0,77,1398650193,0
Paper,"Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis",006d1a3aac3e2ac9ac996592e94287fe22a8dd7d,156311,0,0,39,1398650193,0
Paper,"Boosted Classification Trees and Class ProbabilityQuantile Estimation",5b16ef1142ebaa902bf0b2c0e0fc5c3b5793f1ca,989974,0,0,35,1398650193,0
Paper,"Hierarchical Knowledge Gradient for Sequential Sampling",8fa61f0a8f3d7f90f077633c6519f90a112e157f,594380,0,0,36,1398650193,0
Paper,"Subgroup Analysis via Recursive Partitioning",a5a7097ea1e9a4f1eadfbaafb1c59c9ef579d0d9,143832,0,0,25,1398650193,0
Paper,"A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis",43e3d8cc504a81b9f2d5169a4cdcd6b782e66c0f,577246,0,0,38,1398650193,0
Paper,"Union Support Recovery in Multi-task Learning",d5ec14d9c059a661009328f8e42a8fb8114a72ae,212206,0,0,31,1398650194,0
Paper,"Some Theory for Generalized Boosting Algorithms",8ddc6ba461fcd7847186f19b86033644dfaa61ec,205596,0,0,32,1398650194,0
Paper,"Bayesian Co-Training",87746816742b37abaaaa19d5fe915269d46c2c27,377649,1,0,36,1398650194,0
Paper,"Clustering on the Unit Hypersphere using von Mises-Fisher Distributions",89d043438b621c67d89d46dcca3275739c0ac799,295338,0,0,26,1398650194,0
Paper,"Learning Recursive Control Programs from Problem Solving (Special Topic on Inductive Programming)",df4cf8ef981a46e6b2307e3d80c7134676a3edd2,192325,0,0,35,1398650195,0
Paper,"Graph Laplacians and their Convergence on Random Neighborhood Graphs (Special Topic on the Conference on Learning Theory 2005)",b97150c05da979971d5f724fb88b14ab703d4b35,2911681,0,0,34,1398650195,0
Paper,"Stability and Generalization",1c04354e3b6a4368ec412fd54de9a8e4d59ed30a,210937,0,0,35,1398650195,0
Paper,"A Nonparametric Statistical Approach to Clustering via Mode Identification",076359232032191f2a858982ff463ddfe08b4ea9,665624,0,0,50,1398650195,0
Paper,"Text Classification using String Kernels",4c9c48699f20f3b4b62e59ca927fef79cebdf5e0,202025,0,0,42,1398650195,0
Paper,"Communication-Efficient Algorithms for Statistical Optimization",0710d4361d4ca489c7ca6e500ccce71d7699ebe3,381049,0,0,41,1398650195,0
Paper,"Polynomial-Delay Enumeration of Monotonic Graph Classes",0220f37a4a1cdf8b936d67cb94c4176e66502efa,204986,0,0,32,1398650195,0
Paper,"Learning Coordinate Covariances via Gradients",456bd90c7337fe6f76a6e2fce0374d41b5f46cbe,385958,0,0,32,1398650195,0
Paper,"Operator Norm Convergence of Spectral Clustering on Level Sets",fc7d3a5d7832e95df39a5f5b15ce5f507c7771fa,247312,0,0,30,1398650195,0
Paper,"Asymptotic Model Selection for Naive Bayesian Networks",6690e0941328f9ea8724754e91f0e73a25c85b3e,1078131,0,0,30,1398650195,0
Paper,"Spam Filtering Based On The Analysis Of Text Information Embedded Into Images (Special Topic on Machine Learning for Computer Security)",ad9c48d261d03045f96d3202cf4858fc57b20699,482175,4,0,63,1398650195,0
Paper,"A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning (Special Topic on Model Selection)",c7d9b7be3f7aaa9167cae52a23e800c0e0ef5cea,1130657,0,0,29,1398650195,0
Paper,"A Direct Method for Building Sparse Kernel Learning Algorithms",2e96deb9f1a0b27ff0c3a2fd6d89b83fa47672aa,282870,0,0,34,1398650195,0
Paper,"Learning the Kernel Function via Regularization",6bf074135eaaea73a3e5d6e548b0b31333ab906e,221869,0,0,33,1398650195,0
Paper,"Diffusion Kernels on Statistical Manifolds",4209420e28a999fa898e2305185feb3728d272e9,1337167,0,0,29,1398650195,0
Paper,"Adaptive Subgradient Methods for Online Learning and Stochastic Optimization",d385e01673b699db102a3a362ebb4fba46ee3660,307882,0,0,34,1398650195,0
Paper,"Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization",e0851617cd76e1cfa4de188b713af44ac40816fc,1616302,0,0,29,1398650195,0
Paper,"Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space (Kernel Machines Section)",36e0378030715a494a927af440defed23b2880bf,235157,0,0,33,1398650195,0
Paper,"Faster Algorithms for Max-Product Message-Passing",21b53d95668aa4a95bdde21e4cde68ff9b6d6803,1119635,0,0,35,1398650196,0
Paper,"The Need for Open Source Software in Machine Learning",c859121d01e0ae57fd36488c9a5c529b29815685,1278865,0,0,53,1398650196,0
Paper,"Variable Sparsity Kernel Learning",270fcf02619a09a2adc72c279551898d2e7ae330,236150,0,0,31,1398650196,0
Paper,"Margin-based Ranking and an Equivalence between AdaBoost and RankBoost",6cd0a8f32126a69e15a2cd64214f78ba1d794552,420285,0,0,37,1398650196,0
Paper,"High-dimensional Covariance Estimation Based On Gaussian Graphical Models",b3cd62da6ee16228b9c1065111e49e299d3ab1ae,735000,0,0,34,1398650196,0
Paper,"The Sample Complexity of Dictionary Learning",05ff4e0edd719b5f4665f8f2b4bda672882e6496,185590,0,0,39,1398650196,0
Paper,"Models of Cooperative Teaching and Learning",8c3255d6bad6b7202880db1517458f28afe55254,278164,0,0,63,1398650196,0
Paper,"Maximum Margin Algorithms with Boolean Kernels",7dc07f4ef25da9cd9da379f80e6f88873b9fc6ba,192065,0,0,35,1398650196,0
Paper,"Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss",d69e949c56375d58ede4a94869d91f971e22c59e,122780,0,0,25,1398650196,0
Paper,"Dynamic Weighted Majority: An Ensemble Method for Drifting Concepts",682e6eabe24d0007d9b35df1490e66f211379437,490168,0,0,27,1398650196,0
Paper,"An Anticorrelation Kernel for Subsystem Training in Multiple Classifier Systems",c684ecfe5efb99fd7b4dfeba356e761dbe7d9821,560990,0,0,32,1398650196,0
Paper,"Linear State-Space Models for Blind Source Separation",1d93e447c4599e8d41257cb05574b9fc81b2d1ce,325019,0,0,33,1398650197,0
Paper,"Bilinear Discriminant Component Analysis",4a632373b4f3d101d2991d50a06c30b28f58c9b9,669205,0,0,42,1398650197,0
Paper,"Structure Spaces",61cf92536eea9604d8755af5ee0e712e718f0692,669799,0,0,36,1398650197,0
Paper,"Model Monitor (M2): Evaluating, Comparing, and Monitoring Models(Machine Learning Open Source Software Paper)",537f6b864879a1141c725ccdb56b78efe10bb5d7,169710,0,0,43,1398650197,0
Paper,"Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming (Special Topic on Machine Learning and Optimization)",b430633dd781b7b7357597c66666f9ea73b7be0a,254488,0,0,37,1398650197,0
Paper,"Universal Kernels",966332ffa949ca565e874c3b0c4db39b3bddf2b4,140166,0,0,28,1398650197,0
Paper,"Semigroup Kernels on Measures",50c2c345aacf27cf1065fc09716eb8259b3dcc51,379052,0,0,30,1398650197,0
Paper,"Considering Cost Asymmetry in Learning Classifiers",a9bd8db4e6ddb322259cacaa0c0668f7b6fc1290,355115,0,0,26,1398650197,0
Paper,"Support Vector Clustering (Kernel Machines Section)",676311e19d559eff4c0d65ed23abb7fd143a03d3,326517,0,0,38,1398650198,0
Paper,"Strong Limit Theorems for the Bayesian Scoring Criterion in Bayesian Networks",86baaa1e04744d1efdd63b5627f0cde988b82aae,120693,0,0,34,1398650198,0
Paper,"AdaBoost is Consistent",0eb2fb76eb57bfb05278dcecc6a6b2a297d65dfd,184121,0,0,33,1398650198,0
Paper,"Clustering with Bregman Divergences",db239d92ba00c26cab551146d29f9ce404de4206,342744,0,0,26,1398650198,0
Paper,"Adaptive Exact Inference in Graphical Models",ad910eb28d6a12ce53198743901eb3aac2d6f3d2,644271,0,0,31,1398650198,0
Paper,"Better Algorithms for Benign Bandits",aafc09fd9ad321c97aa4a22a5fe9430375c7323e,186296,0,0,30,1398650198,0
Paper,"Machine Learning with Data Dependent Hypothesis Classes",6ad9ad36edba1929e716dd78101cd00e3fbf6376,145270,0,0,35,1398650198,0
Paper,"Learning Spectral Clustering, With Application To Speech Separation",ceb026d186ec8a3a36151226d8bf3b939d313018,660254,0,0,35,1398650198,0
Paper,"Incremental Algorithms for Hierarchical Classification",8e9fbb3ea861d404bb3ad130f2aa9c970ecc4778,183489,0,0,33,1398650198,0
Paper,"Weisfeiler-Lehman Graph Kernels",cd8ab06b42bef8ed5f3f2fdff35e91caad1ee17f,299278,0,0,26,1398650199,0
Paper,"Machine Learning for Computer Security(Special Topic on Machine Learning for Computer Security)",3eced34cd948e7ea92f31ded3e0fd734274fee4a,59935,4,0,159,1398650199,0
Paper,"Provably Efficient Learning with Typed Parametric Models",aaa2d79273c5aa9e6e5a3d88d5b23f31b1b42884,2486378,0,0,29,1398650199,0
Paper,"Nonparametric Quantile Estimation",8cbd0b0a61916754b4346403670e203f8712437b,904720,0,0,35,1398650199,0
Paper,"Fast Iterative Kernel Principal Component Analysis",a63f5649a1288237c6f5d3904c1999a8c889ab90,3186111,0,0,33,1398650199,0
Paper,"Two Distributed-State Models For Generating High-Dimensional Time Series",d044760b9925a1eb2861475316f5938a6141a2ef,866010,0,0,36,1398650200,0
Paper,"Unlabeled Compression Schemes for Maximum Classes",f939f605369d0dc11ec8ccaf6f472911be5c56d3,457234,0,0,28,1398650200,0
Paper,"The Stationary Subspace Analysis Toolbox",f3210a6851c50793e0b96e20867b5c717cf6d489,70419,0,0,25,1398650200,0
Paper,"The Locally Weighted Bag of Words Framework for Document Representation",b0f8ae49890d4cf83f1f0d2deb274725dba71e32,1737461,0,0,38,1398650200,0
Paper,"Characterizing the Function Space for Bayesian Kernel Models",1ea04a9b83c5a3e90ca3b6ec6db8fd330d6547c6,228847,0,0,34,1398650200,0
Paper,"On Equivalence Relationships Between Classification and Ranking Algorithms",67298f2c214fabd83eab7dd209d6c010e91e040a,376989,0,0,33,1398650200,0
Paper,"Recommender Systems Using Linear Classifiers",540a23376d40d553340e7b44a2ce99efac5215d7,248116,0,0,85,1398650200,0
Paper,"One-Class SVMs for Document Classification (Kernel Machines Section)",8bb752460e3ddecdf5c6e97aef7c4f6300429f35,326603,0,1,26,1398650200,0
Paper,"Efficient and Effective Visual Codebook Generation Using Additive Kernels",7b4b3bbdc638189b68335bfbea6a25ba5fddd0bc,165795,0,0,28,1398650200,0
Paper,"One-Class Novelty Detection for Seizure Analysis from Intracranial EEG",82f2ad2030b66cdb205fa6726dfcb13413963ae0,276869,0,0,35,1398650200,0
Paper,"Efficient Margin Maximizing with Boosting",0a1853a62449b6b58acdcf59914841735ffbb8e6,605342,0,0,43,1398650201,0
Paper,"Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition",42c544de8a7f3e8a6819431fec63283f1add5fe0,271670,0,0,29,1398650201,0
Paper,"Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks",f829b5170f398d4967cb73c21017e35d3f4ca234,147291,0,0,31,1398650201,0
Paper,"Markov Properties for Linear Causal Models with Correlated Errors(Special Topic on Causality)",91c569762ad4c2cee8abb9afab37b8e5cff93f6a,231172,0,0,29,1398650201,0
Paper,"Maximum Entropy Discrimination Markov Networks",a8bee85a0b8dcd390e3623c7db0a27f43222659b,593202,0,0,25,1398650201,0
Paper,"On Efficient Large Margin Semisupervised Learning: Method and Theory",7d806d1b2f4361971692c59b3862d2bad741ce78,630897,0,0,28,1398650201,0
Paper,"Concentration Bounds for Unigram Language Models",c13eb0babbc742a76ffbddc13ff61cba5f32e8e5,219415,0,0,29,1398650201,0
Paper,"Exact Simplification of Support Vector Solutions (Kernel Machines Section)",b0441320a6eeb7f16b4dbad0a762d48bbcbdb5cd,332061,0,0,30,1398650201,0
Paper,"A Near-Optimal Algorithm for Differentially-Private Principal Components",968f1af6a402ac653871675029d2bf9444d5d3aa,424726,0,0,34,1398650201,0
Paper,"Regression on Fixed-Rank Positive Semidefinite Matrices: A Riemannian Approach",881e10e2a8109bc3c4c343e199fafdce1ba47e72,340672,0,0,31,1398650201,0
Paper,"Statistical Consistency of Kernel Canonical Correlation Analysis",addad9344cac172f38057eac4c68c2dc19ae1813,367796,0,0,30,1398650201,0
Paper,"Kernel Analysis of Deep Networks",5975549bc2e7cc159af7906844199fc8ac59c425,762619,0,0,79,1398650201,0
Paper,"Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation",987a4a59d5e3361d945c18d53ccc12beabb05598,140340,0,0,29,1398650201,0
Paper,"A Stochastic Algorithm for Feature Selection in Pattern Recognition",cdb0f212f1ab2bfc77c8280174c2a32bfc640cf0,438674,0,0,48,1398650202,0
Paper,"On the Consistency of Multiclass Classification Methods (Special Topic on the Conference on Learning Theory 2005)",7858fdf307d9fe94aeaaeaeadfc554988b80a3ce,174763,0,0,29,1398650350,0
Paper,"Learning to Select Features using their Properties",0baade895c487724dc4e1bb3c00ac01436c9f767,137755,1,0,35,1398650693,0
Paper,"A Multiple Instance Learning Strategy for Combating Good Word Attacks on Spam Filters",72be7eb406e778d33a811ee00b4c2f16bb298670,281478,0,0,28,1398650693,0
Paper,"HPB: A Model for Handling BN Nodes with High Cardinality Parents",dd8607dea92a1f40c2fbf0ced40717a4101d15ef,306205,0,0,22,1398650693,0
Paper,"Model Selection in Kernel Based Regression using the Influence Function(Special Topic on Model Selection)",0db504995fe64f0dca400a11f146ba007da5bcce,264412,0,0,33,1398650693,0
Paper,"Minimal Nonlinear Distortion Principle for Nonlinear Independent Component Analysis",04b87a940d20054d7b8e8517b07594be39a22451,2913342,0,0,36,1398650693,0
Paper,"Complete Identification Methods for the Causal Hierarchy(Special Topic on Causality)",494f67d57abb4a2b2a1569d0957c8465737e35a2,495052,0,0,35,1398650693,0
Paper,"Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers",903a5ecb011e8d9af24933ebe07cbe50e1f07be2,449201,0,0,34,1398650694,0
Paper,"Gradient Tree Boosting for Training Conditional Random Fields",7199cf9eaca3c451860febeafe48565ea1b35a54,2504832,1,0,39,1398650694,0
Paper,"Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks",07778ccabf041692ac10728350a99310ad4bcce0,252227,0,0,29,1398650694,0
Paper,"Active Learning by Spherical Subdivision",9e38b71ba22a194b1ed0008950d2fef430f7b8e8,560527,0,0,32,1398650694,0
Paper,"Nearly Uniform Validation Improves Compression-Based Error Bounds",6dee60ca650e69104ca00cddcfa37d1bf4f24662,194191,0,0,28,1398650694,0
Paper,"Discriminative Learning of Max-Sum Classifiers",375896cb5a477b789da29b77101d39cbda5ac916,1533844,0,0,29,1398650694,0
Paper,"Multi-class Discriminant Kernel Learning via Convex Programming(Special Topic on Model Selection)",2564fc98f00cee827e978026078e996d71540995,269352,0,0,35,1398650694,0
Paper,"Automatic PCA Dimension Selection for High Dimensional Data and Small Sample Sizes",d5c9aa310bbaa11f7ce67c5293e760e558207019,3716712,0,0,33,1398650694,0
Paper,"Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction",64a22f796592c79060c833e8f4f43b57a58e22df,441498,0,0,41,1398650694,0
Paper,"Ranking Categorical Features Using Generalization Properties",944422ba09b0a06697855b56bdb2cbb8d7d8c399,449954,0,0,31,1398650694,0
Paper,"Visualizing Data using t-SNE",9637de2f50952d9d8f52ac301ef04adef7fc7e4e,254269,0,0,26,1398650694,0
Paper,"Non-Parametric Modeling of Partially Ranked Data",530abae83beab7b0c28ada2b2e0c05c501368e39,390105,0,0,27,1398650694,0
Paper,"Learning Similarity with Operator-valued Large-margin Classifiers",fe7472920bcae4ff936715f160f4d19a91500a45,197461,0,0,25,1398650694,0
Paper,"Trust Region Newton Method for Logistic Regression",6c04924c144aa652a22729992fc90c87029fbd5e,48849,0,0,31,1398650694,0
Paper,"Linear-Time Computation of Similarity Measures for Sequential Data",0b94baebf5c94c37b3aac5ae0b1ea64e45712537,533677,0,0,32,1398650694,0
Paper,"On Relevant Dimensions in Kernel Feature Spaces",774436c940f047c67a4c7266b56706f0a0725f76,102561,0,0,24,1398650694,0
Paper,"Learning Control Knowledge for Forward Search Planning",ca5b3f4c71025c801cf3383bf4ade2e3a09f2f54,203047,0,0,27,1398650694,0
Paper,"On the Size and Recovery of Submatrices of Ones in a Random Binary Matrix",8395af658162b29ab6723ab13822a7ca17d6341b,856271,0,0,28,1398650694,0
Paper,"On the Suitable Domain for SVM Training in Image Coding",81a47ae86153d940580a01017b040da445bc28da,521356,0,0,33,1398650694,0
Paper,"SimpleMKL",9a7b033a7a12876bb4b7b2376d9b28e1518cbe99,843949,0,0,32,1398650695,0
Paper,"Finite-Time Bounds for Fitted Value Iteration",5e3d93e553bb1471433e36e94ad686d07f2b3eca,54732,0,0,29,1398650695,0
Paper,"Learning from Multiple Sources",a91d148d082332f0c0b2231c6a08cc7c2869bf69,510004,0,0,32,1398650695,0
Paper,"Randomized Online PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension",1b397cb54c2bb0378b38b64935ea868a8a109183,306689,0,0,49,1398650695,0
Paper,"Bayesian Inference and Optimal Design for the Sparse Linear Model",cd9896d409b4ff16a1c2bcb1d3c51ec2147787ae,448970,2,0,155,1398650695,0
Paper,"Finding Optimal Bayesian Network Given a Super-Structure",59975e2fe7358266a56dcf58b568c8792749dfaa,356667,0,0,34,1398650695,0
Paper,"A Moment Bound for Multi-hinge Classifiers",ebe3027120419d2ae25dee559946f954b0271be0,4119696,0,0,32,1398650696,0
Paper,"Learning Balls of Strings from Edit Corrections",6e8a90310cafa2984f6d6754ad83a60d5b35e5f2,648887,0,0,35,1398650696,0
Paper,"Value Function Based Reinforcement Learning in Changing Markovian Environments",26d1ed2e2fae81bb304ee38baeb6ac7da155d7ed,382697,0,0,31,1398650696,0
Paper,"An Error Bound Based on a Worst Likely Assignment",b731c15f0c42e454ec96775d8f3a6ddcd6409ff9,163133,0,0,26,1398650696,0
Paper,"Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data",76ea1046a70ebe6bfacd53fee64ed6e22835391d,284292,0,0,32,1398650696,0
Paper,"Probabilistic Characterization of Random Decision Trees",cf742ce887877ed5fd5e5f52526bcbe30c222b00,231522,0,0,34,1398650696,0
Paper,"Learning to Combine Motor Primitives Via Greedy Additive Regression",66a93322d0218625ab3e86c285af5e15bf051c09,1883581,0,0,31,1398650696,0
Paper,"An Information Criterion for Variable Selection in Support Vector Machines(Special Topic on Model Selection)",ce3807fa7cfe63dc402cea83a8f5d900fd7cd458,764429,0,0,37,1398650696,0
Paper,"Support Vector Machinery for Infinite Ensemble Learning",13837aac7d63d8f20681f7e6d6af6d0495b06cc7,153849,0,0,32,1398650697,0
Paper,"Online Learning of Complex Prediction Problems Using Simultaneous Projections",f784e9f849bc0f4142145161b23ec7cf181ef026,490020,0,0,44,1398650697,0
Paper,"Closed Sets for Labeled Data",bc40153090478105e03845c9168eef0fe41de929,546173,0,0,29,1398650697,0
Paper,"Value Function Approximation using Multiple Aggregation for Multiattribute Resource Management",5950e2f9531fcafd052a29e6253fced3d0e29fe6,1338397,0,0,38,1398650697,0
Paper,"Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective",378f768db789e965e18e82e6537655a4bd37fe12,293983,0,0,46,1398650697,0
Paper,"Multiple-Instance Learning of Real-Valued Data",936a92932c01c3f5e9994ae8bd2115f4ccb4adc9,7100,0,0,31,1398650697,0
Paper,"Multi-Agent Reinforcement Learning in Common Interest and Fixed Sum Stochastic Games: An Experimental Study",905a1856ae59c83e46961c39774a98d5e93b6f5d,31044,1,0,40,1398650697,0
Paper,"Aggregation of SVM Classifiers Using Sobolev Spaces",a717b062ca3e26c659a513eb1cf48a2d7e760697,197605,1,0,34,1398650697,0
Paper,"Minimal Kernel Classifiers (Kernel Machines Section)",6c07eeed3d15b409e1e61afb2f35998f787f678e,408146,1,0,52,1398650697,0
Paper,"Mixed Membership Stochastic Blockmodels",2d9fa4c14ce0ea510fcbb35cdf2c1c026596dcaf,140425,1,0,36,1398650697,0
Paper,"Data-dependent margin-based generalization bounds for classification",28a4a9d084522d1bf2ffeb3163e2e771a8f8f34c,298604,1,0,38,1398650697,0
Paper,"Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming",28acd76f57bb2194087ef9a57b13d6a4adb2edb5,275986,1,0,38,1398650697,0
Paper,"Causal Reasoning with Ancestral Graphs(Special Topic on Causality)",b19ab3f5b9d697fabd43259db5dc42948356adc3,728929,1,0,36,1398650697,0
Paper,"Robust Submodular Observation Selection",eaf6521c44b5ca8db8d93c57b324ff4c35b34f32,25343849,1,0,52,1398650697,0
Paper,"Magic Moments for Structured Output Prediction",1c4fbdb2caa3b21d17d20cb8c001e434ceaec178,264130,1,0,35,1398650697,0
Paper,"Search for Additive Nonlinear Time Series Causal Models",bc6a95f3a1ec7d89e52d1e6a4ae661dbaa769985,784415,1,0,39,1398650697,0
Paper,"Learning Precise Timing with LSTM Recurrent Networks",f018ed13be7e4ca2f00b740524c3b36d5196cf55,341852,1,0,51,1398650698,0
Paper,"Grafting: Fast, Incremental Feature Selection by Gradient Descent in Function Space (Kernel Machines Section)",f31b0ef2048424d3b7b66538d6c4da6f7a3c5db5,253433,2,0,52,1398650698,0
Paper,"A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification (Kernel Machines Section)",244c23e3a7062823ef49de70eab0eb51f2c3468c,301961,0,0,34,1398650698,0
Paper,"Learning to Construct Fast Signal Processing Implementations",f7ae3b62362210a54498015cbc5f94db1ea2ee4d,283990,1,0,36,1398650699,0
Paper,"Use of the Zero-Norm with Linear Models and Kernel Methods (Kernel Machines Section)",8a36766d87a75f389fa1aa990fa71f0731363b9a,230272,1,0,38,1398650699,0
Paper,"Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning",757245e31fd10a11c8794d3384dbffbdf97fd1e1,2179310,1,0,33,1398650699,0
Paper,"Distributional Word Clusters vs. Words for Text Categorization (Kernel Machines Section)",658627300dd23648f58177f238327eb0832871c1,140095,1,0,39,1398650699,0
Paper,"Online Submodular Minimization",5533d2cdec46d72ab67cc9126cf262b8ac6be883,140144,1,0,30,1398650699,0
Paper,"Structural Learning of Chain Graphs via Decomposition",677280641c8076dda3e04887360a272b2405ab0a,809442,1,0,35,1398650699,0
Paper,"A Tutorial on Conformal Prediction",350b9cfb3613f55812577cf980465694de9cdc74,75336,1,0,42,1398650699,0
Paper,"Stationary Features and Cat Detection",5b025381a593836a068f13e3b07f039dd4e5222f,286029,1,0,34,1398650699,0
Paper,"-MDPs: Learning in Varying Environments",3634303099110d62a04931a61d765db4eafe994d,292579,1,0,40,1398650699,0
Paper,"Graphical Models for Structured Classification, with an Application to Interpreting Images of Protein Subcellular Location Patterns",a84843e9bb71109eff0386b39acb4f70a58b4d04,162578,1,0,38,1398650699,0
Paper,"Rademacher and Gaussian Complexities: Risk Bounds and Structural Results",e2c999aee9996bdd2ec49ee83c38cf51680c4e45,309448,1,0,31,1398650699,0
Paper,"Learning Probabilistic Models of Link Structure",05efe66eb343ac4873beadfff6fc89df0ab83eb4,1989259,1,0,44,1398650699,0
Paper,"DEAP: Evolutionary Algorithms Made Easy",ac9a858e4781b9b8a0acb2d12a4ef291e6509fa9,302542,1,0,71,1398650699,0
Paper,"Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem",0de748dc086791b5cde497b0dca4e896614a7d69,274080,1,0,41,1398650699,0
Paper,"The Set Covering Machine",d7e14370bebe943dc6a4cef89a742de52a6a28c4,599848,1,0,36,1398650699,0
Paper,"Optimization Techniques for Semi-Supervised Support Vector Machines",239d78675e2c2f64f5d6544ff85b5d206f451a26,48167,1,0,36,1398650700,0
Paper,"On Boosting with Polynomially Bounded Distributions",329dd577181e340c38c987edcf47906ce5700777,285321,1,0,29,1398650700,0
Paper,"JNCC2: The Java Implementation Of Naive Credal Classifier 2(Machine Learning Open Source Software Paper)",abe316b76c07662377614dd1d3deeaf7bbd4abfb,184931,1,0,92,1398650700,0
Paper,"Efficient Algorithms for Decision Tree Cross-validation",f6084af01c3b5f141357da7650a46652b7819e22,1012368,1,0,48,1398650700,0
Paper,"Learning Symbolic Representations of Hybrid Dynamical Systems",f41f4f536d2b60782911e1bfa257078d23465384,1985417,1,0,39,1398650700,0
Paper,"An Introduction to Artificial Prediction Markets for Classification",d410f824cb7401a3b0f341279e0e4947cc5f6105,382028,2,0,108,1398650700,0
Paper,"Rejoinder to Reponses to Evidence Contrary to the Statistical View of Boosting",afff4d2d8d6638904760b72dfd7025a031e7562d,362151,1,0,29,1398650700,0
Paper,"An Improved GLMNET for L1-regularized Logistic Regression",7e2714ef3c9935f7b69f3d340e2c87de325b2cd2,549240,2,0,47,1398650700,0
Paper,"Positive Semidefinite Metric Learning Using Boosting-like Algorithms",4b9d141736b5842aa7e384fc1e83e7acd5f815b1,520965,1,0,32,1398650700,0
Paper,"Kernel Methods for Relation Extraction",7856d9f782cdb73ed80434bc67777063090a0032,1699537,1,0,43,1398650700,0
Paper,"Structured Sparsity and Generalization",ceebd84f2e899b59b7210e16cca72f598dffd293,146956,1,0,32,1398650700,0
Paper,"Learning Monotone DNF from a Teacher that Almost Does Not Answer Membership Queries",5a5ca85b282b3b1847523789aa7e164d9a7d83c6,151732,1,0,37,1398650701,0
Paper,"Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices",d7a243353eec534de466eeb3f2f40b51d9ae2895,395104,1,0,33,1398650701,0
Paper,"A Case Study on Meta-Generalising: A Gaussian Processes Approach",98cf97e5ff54db7b6d12d0b4f98e7002feddad7e,390476,1,0,39,1398650701,0
Paper,"Nonparametric Guidance of Autoencoder Representations using Label Information",53924a521b9c9d67c89a2da3fa8e8f8f1f1c3937,816490,1,0,34,1398650701,0
Paper,"Ranking a Random Feature for Variable and Feature Selection",c65d372e2a2e00f1ff3608764a18a66708ed5cab,142448,2,0,37,1398650701,0
Paper,"Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions",f5c1c6514a5d6adb80fe84966ee28e5d8294f83d,29619,1,0,35,1398650702,0
Paper,"Optimistic Bayesian Sampling in Contextual-Bandit Problems",0b5365e25cf26e1a7592b634ead614db82ed6031,9990704,1,0,55,1398650702,0
Paper,"NIMFA : A Python Library for Nonnegative Matrix Factorization",636e004329b9da7452feab9e543c7bca2a3af65f,35812,2,0,78,1398650702,0
Paper,"Finite-Sample Analysis of Least-Squares Policy Iteration",a0980d654eec0d65bfd5d0fb15c04141b46eb5c7,290026,1,0,33,1398650702,0
Paper,"Ranking Individuals by Group Comparisons",3540028f12669876e8c36cc9cc7bbd38ed239e22,158945,1,0,35,1398650702,0
Paper,"MedLDA: Maximum Margin Supervised Topic Models",52bb0a07bf9bf6bda93e6178b42bcf3a4e9360a0,1321456,1,0,38,1398650702,0
Paper,"EP-GIG Priors and Applications in Bayesian Sparse Learning",b590650675dc8b49b4562bd82144f5649c2f6b29,1228428,2,0,34,1398650702,0
Paper,"Structured Sparsity via Alternating Direction Methods",076ca91cc7f0bd7bb802b6622a5d46ec49b280ea,629885,1,0,45,1398650703,0
Paper,"An Introduction to Variable and Feature Selection (Kernel Machines Section)",29d693fc13be423a38598a7d000c933185f29c90,763446,1,0,45,1398650703,0
Paper,"Large-Sample Learning of Bayesian Networks is NP-Hard",9a4b9f335fc34e1926309b3c6d81900cefe850ce,342067,2,0,60,1398650703,0
Paper,"Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2",f62507cd6f2f5fd5a248b3f43706d8909be1b27d,267556,1,0,31,1398650703,0
Paper,"Multi-Target Regression with Rule Ensembles",e363d82858aa3aea8a32cad442a29ac8d243b333,328302,1,0,32,1398650703,0
Paper,"Static Prediction Games for Adversarial Learning Problems",cdd39295089b63185ca2fb6009858297a3125d0b,619681,1,0,40,1398650703,0
Paper,"Coupled Clustering: A Method for Detecting Structural Correspondence",31bb1d49aa29c536ff8f4edfbb1ae35fdf766135,111017,2,0,54,1398650703,0
Paper,"The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces (Kernel Machines Section)",309dbeb9e5cd88d8bc7ad02d109dd5674549adea,675842,1,0,44,1398650703,0
Paper,"High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion",85d39ec1436373da7c96212f48c59c7f50acc651,380313,1,0,36,1398650703,0
Paper,"A New Algorithm for Estimating the Effective Dimension-Reduction Subspace",b8da80a6506bb92ee0361848b4106e2de6aec52d,292054,1,0,38,1398650703,0
Paper,"Multi-Instance Learning with Any Hypothesis Class",cd9c87f148a42e541d41ac5356c359309a8049f9,328574,1,0,37,1398650703,0
Paper,"Randomized Variable Elimination",8177336f115e53e3de8a416b97194bfe26e84e6d,386372,1,0,35,1398650703,0
Paper,"The Sample Complexity of Exploration in the Multi-Armed Bandit Problem (Special Topic on Learning Theory)",1e3a97735443c7592be48b78733f2349ee0b403f,174521,1,0,39,1398650704,0
Paper,"The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins",af7c1049149f10db2ade5a6b9d9b6fecdcecb0a1,168449,1,0,41,1398650704,0
Paper,"Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction",923d25dc1171104ed2a862fbdfc218ff56f5aa68,184334,1,0,46,1398650705,0
Paper,"Tracking the Best Linear Predictor",c09e7c3fba6fcc802002d6f9a15fe54d8dee5a94,476946,2,0,62,1398650705,0
Paper,"Linear Regression With Random Projections",eb003a400246f6e364bf3ac0bb44067055988bd4,586305,1,0,47,1398650705,0
Paper,"Jstacs: A Java Framework for Statistical Analysis and Classification of Biological Sequences",9ff938b61ed7b5e3d5ebfe3278ce56bd5cc5a3f2,184052,2,0,66,1398650706,0
Paper,"Feature Selection for Unsupervised Learning",9fe1df0d4a7ded57d447c97318b35e60810e32a2,317561,0,0,33,1398650706,0
Paper,"Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions",deb20678ef8a6bbb391b199cafc48998a39ffc1d,2093826,0,0,35,1398650706,0
Paper,"Learning the Kernel Matrix with Semidefinite Programming",2d9247a0b27d6f1130bdcd8b869830ecd8c6243e,386567,0,0,50,1398650706,0
Paper,"In Defense of One-Vs-All Classification",39551e7bd5f0af1f567a2fef9413938c566f0d3b,73107,0,0,29,1398650706,0
Paper,"Learning Ensembles from Bites: A Scalable and Accurate Approach",76fb996864ee7fd80e65c8f6fe44478bb12bbd71,452372,0,0,38,1398650706,0
Paper,"MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling",2e520073db4ce011c5a05d5a8b08496d47865f9f,183688,0,0,36,1398650706,0
Paper,"Fast String Kernels using Inexact Matching for Protein Sequences",cd5521215c0dc806e8eba38813d34d8263c5ee3c,142587,0,0,43,1398650706,0
Paper,"Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection",2c623a098b9f668b9501b3606ab5f94034d81396,706101,0,0,48,1398650706,0
Paper,"Feature Discovery in Non-Metric Pairwise Data",fad3010c2d13bf634f90b8c452e96742d6d6bcc7,255361,0,0,31,1398650707,0
Paper,"An Approximate Analytical Approach to Resampling Averages (Kernel Machines Section)",0460c8c1896c195a47791759abe21686cbb59962,3158908,0,0,38,1398650707,0
Paper,"On the Convergence Rate of lp-Norm Multiple Kernel Learning",5cf922c6e8277a4e554a5370c8066469c238cd48,417134,0,0,41,1398650707,0
Paper,"SVMTorch: Support Vector Machines for Large-Scale Regression Problems (Kernel Machines Section)",e56fbff6604eb9544fd702e368479af155406413,307974,0,0,36,1398650707,0
Paper,"A Unified Framework for Model-based Clustering",818f8f9a9d516aeb11ca86f8df6d0a5a8febfd45,338530,0,0,31,1398650707,0
Paper,"Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters",aaf5ad6fca5f36419ba219aa90bd87c800b18054,3296670,0,0,33,1398650707,0
Paper,"Inducing Grammars from Sparse Data Sets: A Survey of Algorithms and Results",c867c760e4256aafb009cc7e5b9d893430c4f6e4,249819,0,0,26,1398650707,0
Paper,"Benefitting from the Variables that Variable Selection Discards",b388afb9c9ce20102130a3ecdddf4e685e49797d,176224,0,0,28,1398650707,0
Paper,"Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs",294776d4fe640bb3e5ad3dfcd2328f2346c3d0e0,1835220,0,0,34,1398650707,0
Paper,"On Inclusion-Driven Learning of Bayesian Networks",fe662fc45e7629b07622f64444a77b710a5729bb,245651,0,0,26,1398650707,0
Paper,"The Minimum Error Minimax Probability Machine",6ef48588ccadd8a66f4fb57556644b46988251ce,196392,0,0,34,1398650708,0
Paper,"An Efficient Boosting Algorithm for Combining Preferences",776004e8c9e95787577b92fc7d95bd36619ad351,208763,0,0,30,1398650708,0
Paper,"Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence",5f6cc184ae73ffa7eb7e30ebdf5e9f3698c4838a,1715001,0,0,57,1398650708,0
Paper,"Sources of Success for Boosted Wrapper Induction",2e675fd95fd66b8e1ec4484f32b4ac8ea0233257,166046,0,0,31,1398650708,0
Paper,"PAC-learnability of Probabilistic Deterministic Finite State Automata",df1998a71077eb7a760183a3113069ca656304b8,238050,0,0,36,1398650708,0
Paper,"Multi-task Regression using Minimal Penalties",26f1d4b3dd6d99ab4b66c15207ba1c667d83abe1,293140,0,0,33,1398650708,0
Paper,"On the Proper Learning of Axis-Parallel Concepts",9e1cbfb7707e416e8678dbddcd2b8621144e3d8d,190229,0,0,30,1398650709,0
Paper,"Distance Metric Learning with Eigenvalue Optimization",82d7811db75a699d123540f97f5a10ecf82568b0,238075,0,0,33,1398650709,0
Paper,"Kernel Independent Component Analysis (Kernel Machines Section)",9aff3a0db5031f9e10b8262bea3ae30e11d2af3d,481878,0,0,34,1398650709,0
Paper,"Consistency of Trace Norm Minimization",23483f229c9ced5b0e0fe4cf631d06ee881a67d9,168849,0,0,35,1398650709,0
Paper,"Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-Features",6c1daa1fab43805daeddd2c3cb77ab6e2499be05,486136,0,0,41,1398650709,0
Paper,"A Multi-Stage Framework for Dantzig Selector and LASSO",889cda18e25e3f41a8b9252e5449eeda18548b66,246478,0,0,30,1398650709,0
Paper,"Stochastic Composite Likelihood",78716f1d436c9cbc4137a8e4552c596bec1256d7,749141,0,0,29,1398650709,0
Paper,"Weather Data Mining Using Independent Component Analysis",4ff6ef8523a58c14beafa5e99f512e96bc2f6b10,168930,0,0,62,1398650710,0
Paper,"Large Scale Online Learning of Image Similarity Through Ranking",c95e5c45a8cfa5b3b07d7bcce803e7fc5d4c5284,1167567,0,0,28,1398650710,0
Paper,"Incremental Sigmoid Belief Networks for Grammar Learning",0b615aa4e85be044021050e8abf2834a1da2fe28,252380,0,0,38,1398650710,0
Paper,"Active Learning of Causal Networks with Intervention Experiments and Optimal Designs(Special Topic on Causality)",518e14455aa670fa96c89c2fa86421a5e19011a6,233007,0,0,34,1398650710,0
Paper,"Matrix Completion from Noisy Entries",0756c4a008924839bdbb8c0d73113dfa6c636f9d,199962,0,0,50,1398650710,0
Paper,"A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design",a0c9ac85b5d5a386250be4451913a03020e78931,323663,0,0,32,1398650710,0
Paper,"Distance-Based Classification with Lipschitz Functions (Special Topic on Learning Theory)",e66e7c65690698c34045fb6a89085f020a9d5fcf,153013,0,0,31,1398650710,0
Paper,"Combining Knowledge from Different Sources in Causal Probabilistic Models",3b8ce43d2b727fb96fde0ca485c41589d67bc11e,152729,0,0,37,1398650710,0
Paper,"Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds",1b5ba31cd3df0adfc9aaadfac2d4ef13fe6ba423,5479883,0,0,40,1398650710,0
Paper,"Quadratic Programming Feature Selection",109e4b0af9eda299d253009b35086107a18f7c3d,358442,0,0,70,1398650710,0
Paper,"Efficient Feature Selection via Analysis of Relevance and Redundancy",143139de95c2900b81e43253332964e43579eccb,221157,0,0,36,1398650710,0
Paper,"Robust Kernel Density Estimation",8f9e1d5c029a01bdc341af554109ac93a6cb2363,457798,0,0,33,1398650711,0
Paper,"Efficient Algorithms for Conditional Independence Inference",7db911570613fe0e2aca854b562db381906a270a,218063,0,0,35,1398650711,0
Paper,"Generalized Power Method for Sparse Principal Component Analysis",9f3b021d777a45db7a13f44e8bea155b8cb58085,303390,0,0,45,1398650711,0
Paper,"Classification with Incomplete Data Using Dirichlet Process Priors",afb17be0c8af025e713c385fa5ed3d66a4b06c9b,1177307,0,0,30,1398650711,0
Paper,"Manifold Learning: The Price of Normalization",b32416de370acf8ec5131d8f4099675600e114c4,320122,0,0,27,1398650711,0
Paper,"Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation",23d65f7e7c185f595fb4c850f448f6cea7668c28,2425620,0,0,39,1398650711,0
Paper,"Spectral Regularization Algorithms for Learning Large Incomplete Matrices",4fcb51e85df93faa5dd2c8496117c427eaafae8a,569199,0,0,31,1398650711,0
Paper,"Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models",f6ebbdc8e0fb50dae3718ca954f52ccb7adb4047,319906,1,0,31,1398650712,0
Paper,"Classification with a Reject Option using a Hinge Loss",0db1513fac174b28bdb073ea542a430e799bc9ed,299308,1,0,36,1398650712,0
Paper,"Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components",3a3601d50ea073a2b63cd09c243c4854db5f369e,337599,1,0,38,1398650712,0
Paper,"ICA Using Spacings Estimates of Entropy",2f3b72e0452c5e062c9ec69c6a9a4c89c6e454a3,534265,1,0,35,1398650712,0
Paper,"A Fast Hybrid Algorithm for Large-Scale l1-Regularized Logistic Regression",992fc5a3b795a31d6b455b1d62bc010e7a643304,2705447,1,0,40,1398650712,0
Paper,"Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces",74cb0646ae7131abd9a5a74185769d15f0c12959,340159,1,0,36,1398650712,0
Paper,"Matching Words and Pictures",d30c702637eeb68a57def309ace329842069bf93,241452,1,0,34,1398650712,0
Paper,"Introduction to the Special Issue on Learning Theory",26f224552202d280661bf7ddd130bdb9af86c005,411958,1,0,52,1398650713,0
Paper,"An Empirical Study of the Use of Relevance Information in Inductive Logic Programming",9ca794dc4c0c8a6bfce301172ab3aa72b499bd1c,97690,0,0,33,1398650713,0
Paper,"Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes",781510d86759f5991a9a465120e26f4ef5088f6d,300917,1,0,35,1398650713,0
Paper,"Bounding the Probability of Error for High Precision Optical Character Recognition",412368484d2ada74fa61a9671199847e1b8156f3,698793,1,0,45,1398650713,0
Paper,"Online Learning for Matrix Factorization and Sparse Coding",54687040e505d30dc4b9c3243d634089c21ca8f2,4167258,1,0,38,1398650713,0
Paper,"Learning Linear Cyclic Causal Models with Latent Variables",dd421e0587936b94743880c4ffd81401dbb6c372,516046,1,0,33,1398650713,0
Paper,"Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure",4ee1ee4aad1d7f31e33468aa7c9d7ce642ebfe33,295452,2,0,41,1398650714,0
Paper,"Blind Source Separation via Generalized Eigenvalue Decomposition",807ec78c5f243c58f7ecaefe9024be34ce1743d4,546787,1,0,36,1398650714,0
Paper,"Learning Translation Invariant Kernels for Classification",777c5ed841f28d051cfb71b47ab4a8172c7cebc5,398684,1,0,38,1398650714,0
Paper,"Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds",b2f002d5c1b1d7b170c7f4932d7afbb8e8d98793,2013118,1,0,37,1398650714,0
Paper,"Hilbert Space Embeddings and Metrics on Probability Measures",df6ff4362640658f647c606031aa9abda69c079d,530497,1,0,31,1398650714,0
Paper,"Tree-Structured Neural Decoding",ee445f4745a448c0f32fd1531215ce690d3b1867,254186,1,0,34,1398650714,0
Paper,"Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling",569ee0e53edf4e9564861d89d17f052d9dba6087,186164,1,0,47,1398650714,0
Paper,"Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing",7a7ddb4f7ad47182442b2bdd47215e3631970c9c,3362551,1,0,39,1398650714,0
Paper,"Practical Approaches to Principal Component Analysis in the Presence of Missing Values",761fc1338d7f2a89e8547f28208e3ebdfc5c11c2,616991,0,0,39,1398650714,0
Paper,"Second-Order Bilinear Discriminant Analysis",ac52deadf849bcedf323fd472d3c0051caa8c7d4,1120955,0,0,28,1398650714,0
Paper,"Towards Integrative Causal Analysis of Heterogeneous Data Sets and Studies",9ef8e09e06220181e0521d4e4cec1db8ed713233,4046691,0,0,32,1398650714,0
Paper,"Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary -Mixing Processes",2d42e44af64e4da873db06498a34264f0ca4c5f4,237710,0,0,39,1398650714,0
Paper,"Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models",d7a91c029fffd0bcd5aca304fcdfb635d51449df,246473,0,0,24,1398650714,0
Paper,"MULTIBOOST: A Multi-purpose Boosting Package",43ba4aab8e4826a7a678aa7656546074a8fe84e0,40061,0,0,31,1398650714,0
Paper,"An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data",c97acdd2dd26a94a8852d5869affca4b205de689,408002,0,0,38,1398650715,0
Paper,"Consistency of Random Forests and Other Averaging Classifiers",9261b13dd1a091906c79f51af274e57650583679,235857,0,0,37,1398650715,0
Paper,"Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics",7a225973c264012100cb17c5b36f645c3689436b,2442076,0,0,34,1398650715,0
Paper,"Dynamic Policy Programming",29bf1e4d0803773356b58ba5c6727b75eb2212d7,360042,0,0,41,1398650715,0
Paper,"WEKAExperiences with a Java Open-Source Project",435721f87df3273b5fd212ba43664f28946844ca,216113,2,0,110,1398650715,0
Paper,"Beyond Independent Components: Trees and Clusters",e377facbfe5a4a2fb8a80cd62fe9bb6b0c64b7ed,239111,0,0,34,1398650715,0
Paper,"How to Explain Individual Classification Decisions",783985a34ad124c9f34c3cdc1c9e1e44daf3daf3,1639263,0,0,27,1398650715,0
Paper,"Training and Testing Low-degree Polynomial Data Mappings via Linear SVM",4eae73f4109e57ed37f44dd42abca3994cbbc709,150509,0,0,36,1398650715,0
Paper,"Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation",2f4baef4b5a92f3bf9b9b0ee8cdbdf350734eb53,339800,0,0,43,1398650715,0
Paper,"Maximum Relative Margin and Data-Dependent Regularization",db869ba2cbad69ec5a64e02097e4883caf786755,466217,0,0,26,1398650715,0
Paper,"Tree Decomposition for Large-Scale SVM Problems",7fb05f96b721e34657763f2902d2acd2063393f9,403781,0,0,39,1398650715,0
Paper,"Mean Field Variational Approximation for Continuous-Time Bayesian Networks",38d6a74592f397d2b774b947d8e01630fab544d8,1123543,0,0,31,1398650716,0
Paper,"Learning over Sets using Kernel Principal Angles (Kernel Machines Section)",fa48547a07c7bd76260da274c8502ce2a8e2ce0b,144512,0,0,29,1398650716,0
Paper,"Image Categorization by Learning and Reasoning with Regions",fb6a9936f3cf21537b29a8a99dea5c3877ee6d91,149864,0,0,34,1398650716,0
Paper,"Policy Search using Paired Comparisons",0492ad5e1760d75603445e1cbf927c68ee038059,178543,0,0,33,1398650716,0
Paper,"Optimal Distributed Online Prediction Using Mini-Batches",3d011e776f9208473622f1274fc4185b92b2186d,334874,0,0,40,1398650716,0
Paper,"Integrating a Partial Model into Model Free Reinforcement Learning",a130a36bb43f6138f9d10200d127650dd97d954b,328430,0,0,34,1398650717,0
Paper,"A Streaming Parallel Decision Tree Algorithm",6c9fde0154c251f556e2c6f0a674a0105b2f7c74,512654,0,0,52,1398650717,0
Paper,"The Entire Regularization Path for the Support Vector Machine",604e5a5844751bf804cb2b146eb4c6294efa1bd3,184623,0,0,34,1398650717,0
Paper,"Forecasting Web Page Views: Methods and Observations",1f25f4cf7b6c1c3a8284e0b9b3e78b996af9df5c,2499506,0,0,43,1398650717,0
Paper,"Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes",588ba0985c4ccb4026bf3f460d8831468842bd62,553636,0,0,39,1398650717,0
Paper,"On Learning with Integral Operators",36cfb59ec3fe0fccd5171f44b1c1a93a40941001,229281,2,0,44,1398650717,0
Paper,"Multi Kernel Learning with Online-Batch Optimization",f2c29885d2175c129188959ca2dcc24e11e09bbd,351513,0,0,30,1398650717,0
Paper,"Error-Correcting Output Codes Library",85dbb42e94f90e3e0f9387458f384205a788839a,95186,0,0,30,1398650717,0
Paper,"Near-optimal Regret Bounds for Reinforcement Learning",4f529518067fdcaebcd7a132ca84a640d1571b8a,358457,0,0,34,1398650717,0
Paper,"RCV1: A New Benchmark Collection for Text Categorization Research",7e86d470f7a4cd0b370c141b7ed6cf6ca7ff170c,394830,0,0,37,1398650718,0
Paper,"Optimal Solutions for Sparse Principal Component Analysis",f95e296ad0515cd337e57a3df881f37763e54eae,308863,0,0,32,1398650718,0
Paper,"Generalization Error Bounds for Bayesian Mixture Algorithms",b859c3d5df15627e2bbce1b49b2ce0060d23a55f,160178,0,0,32,1398650718,0
Paper,"Model Selection: Beyond the BayesianFrequentist Divide",ae655426e6cb2851f2bc3d75d41ee454acf2ac5a,222720,0,0,30,1398650718,0
Paper,"Relational Learning as Search in a Critical Region",dabb4d1d3f16a74959bc65e6afb90da5c5382d1a,100204,0,0,33,1398650718,0
Paper,"The SHOGUN Machine Learning Toolbox",e210ec5a3ea46b557b4c798321e8712ba6f777e9,37239,0,0,38,1398650718,0
Paper,"Regularization Techniques for Learning with Matrices",9886b06e76eca2473eed4df2e7370715c9e2ce13,242012,0,0,30,1398650718,0
Paper,"LIBLINEAR: A Library for Large Linear Classification(Machine Learning Open Source Software Paper)",e20417f5f84f61a5aa948854fb3ca0e833116462,1430056,0,0,46,1398650718,0
Paper,"Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity",a29d48ae0fca43488819fa4e74165a7b69f54536,245623,0,0,30,1398650718,0
Paper,"Gaussian Processes for Machine Learning (GPML) Toolbox",1574823977be15943c4505c7e51c3b1482f12051,55052,0,0,50,1398650718,0
Paper,"Discriminative Hierarchical Part-based Models for Human Parsing and Action Recognition",c1ce30cc08e90c43ce7971ff45269699bc8fbfe8,9089811,0,0,36,1398650718,0
Paper,"Kronecker Graphs: An Approach to Modeling Networks",faf09d55b358bb0af3e792b866a9225023afd00a,1291957,0,0,39,1398650718,0
Paper,"Permutation Tests for Studying Classifier Performance",6fc40198ba0ab0706759c533a28001804a377c8b,295573,0,0,33,1398650719,0
Paper,"On the Foundations of Noise-free Selective Classification",d6ba8863427fcdd7f8f73de75385ee61c3dbf0e4,552991,0,0,28,1398650719,0
Paper,"PyBrain",22aeae981371179668f128d97c62ac9f4435f605,71138,0,0,50,1398650719,0
Paper,"On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition",59655ff68200d472c491cc2b8b8112275e3ff3f6,488218,0,0,33,1398650719,0
Paper,"Speedup Learning for Repair-based Search by Identifying Redundant Steps",35f46d5b8f8f76d4e211ecdda423242b6057c382,167449,0,0,32,1398650719,0
Paper,"The em Algorithm for Kernel Matrix Completion with Auxiliary Data",8056737d81e1a9ff89e3b6566a7f69aa37a60e09,144745,0,0,30,1398650719,0
Paper,"Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints",ed4dd1fe07fa81d93667cb6c6adf9ce6147f4ed5,230612,0,0,45,1398650719,0
Paper,"Matched Gene Selection and Committee Classifier for Molecular Classification of Heterogeneous Diseases",7f9333199bf3ce69d5e58e7f7cc86489ed4c6c98,548809,0,0,41,1398650719,0
Paper,"Classification Methods with Reject Option Based on Convex Risk Minimization",26cdc093869bf1be51b954dec56c5ec2c3fdbc93,123287,0,0,36,1398650719,0
Paper,"Some Properties of Regularized Kernel Methods",930280d0918a2b8941c035ccf0aa642e8cfe1152,215967,0,0,30,1398650719,0
Paper,"An Exponential Model for Infinite Rankings",6db71aa8d73c2cc65af35047167008da0a746d08,392923,0,0,39,1398650719,0
Paper,"Evolving Static Representations for Task Transfer",efdec7ba0c0770923e79325ab0e34c20784d9279,9964124,0,0,32,1398650719,0
Paper,"Tracking a Small Set of Experts by Mixing Past Posteriors",31c61e72eab7361db5abfae6e0ba8dfb5140e3a4,64739,0,0,30,1398650720,0
Paper,"Dependency Networks for Inference, Collaborative Filtering, and Data Visualization",d8552c6f745b8000a052c9fcb09635e97bc63521,294245,0,0,35,1398650720,0
Paper,"Introduction to the Special Issue on Inductive Logic Programming",e5383c8d7ddc65c489aedfd1fbbc73f053c81f87,708772,0,0,39,1398650720,0
Paper,"Oger: Modular Learning Architectures For Large-Scale Sequential Processing",6c1060c9dca64d64c7f633f9a8b03cdf7beed258,114319,0,0,34,1398650720,0
Paper,"Query Transformations for Improving the Efficiency of ILP Systems",d15b116c906d3995979b99e5f143658e60327e84,337196,0,0,34,1398650720,0
Paper,"Efficient Algorithms for Universal Portfolios",c44653bbc9769fd294d332795c3f0c85a658617b,358863,0,0,35,1398650720,0
Paper,"A Maximum Likelihood Approach to Single-channel Source Separation",aa50815201cdf7090d85b151413fe33009ad4075,738334,0,0,32,1398650720,0
Paper,"SVDFeature: A Toolkit for Feature-based Collaborative Filtering",39fba4740d1db0ce4c2a28ea41c7e1e4d609a728,224993,0,0,34,1398650721,0
Paper,"ICA for Watermarking Digital Images",9f40e4061d1c70a8ef6e0c828c1f7f4f4b64648b,3443364,0,0,38,1398650721,0
Paper,"A Generative Model for Separating Illumination and Reflectance from Images",58f00d4652cd7b5b5a238c5562a977a39183defa,511408,0,0,37,1398650721,0
Paper,"Active Clustering of Biological Sequences",9dd1a91e17e2294624f643e3f1073cb26aa39a2c,332472,0,0,47,1398650721,0
Paper,"Learning Rates for Q-learning",3459786202aa807fde4498d1b85fad02d314d94a,225646,0,0,31,1398650721,0
Paper,"A Rotation Test to Verify Latent Structure",20034c6750ff4bc08205ca738a7a4c8e284c2025,291841,0,0,39,1398650721,0
Paper,"Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods",c741c15c75d92ec8b37cd9b2d3ef157f3acde647,345177,0,0,33,1398650722,0
Paper,"Subgroup Discovery with CN2-SD",5c7183e8c3f23ead7dcdfc70340120d312e779f9,133485,0,0,36,1398650722,0
Paper,"Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications",12dec74bab119eaa23a0ced63349ba6e35cf8656,264275,0,0,35,1398650722,0
Paper,"Consensus-Based Distributed Support Vector Machines",4194b6f476aedf6b101d5e4d3a99159ac9d5c076,1057788,0,0,33,1398650722,0
Paper,"Non-Sparse Multiple Kernel Fisher Discriminant Analysis",c3eee4a1e43d2ab0d8cf860eb77f3d2af076bd5e,555623,0,0,38,1398650722,0
Paper,"The huge Package for High-dimensional Undirected Graph Estimation in R",b33984a3ffa7a931e34d2af393becbeda77c2bf1,339261,0,0,33,1398650722,0
Paper,"Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion",4455093da9243e81e4d23bcef57178a917f6c183,1392544,0,0,67,1398650722,0
Paper,"ML-Flex: A Flexible Toolbox for Performing Classification Analyses In Parallel",204a7af1ec7aafcf1c7a37102d4b353a93620f2d,37007,1,0,34,1398650722,0
Paper,"MOA: Massive Online Analysis",fa2f814f97e6425ee42f63859c96ff4f80002919,82214,0,0,38,1398650722,0
Paper,"Dimensionality Reduction via Sparse Support Vector Machines (Kernel Machines Section)",fdb1fb6a9897eb597328eaa81b648bd8fc5d1ec0,200162,0,0,30,1398650722,0
Paper,"Introduction to the Special Issue on the Fusion of Domain Knowledge with Data for Decision Support",58d212578d6b6432a113f6dd3ef0b1a3c528cf9f,11696,0,0,35,1398650722,0
Paper,"Learning From Crowds",c7e94383a95f855df08531e30bfcb717924baa8b,238950,0,0,38,1398650722,0
Paper,"Rate Minimaxity of the Lasso and Dantzig Selector for the lq Loss in lr Balls",ba4ad580df0ca2517cd8ea20551bc2645bbf573f,201788,0,0,28,1398650722,0
Paper,"Query Strategies for Evading Convex-Inducing Classifiers",f3bdf58e2eea2c35c9066a1e5fcbcd2b62d142e7,374135,0,0,31,1398650723,0
Paper,"Sign Language Recognition using Sub-Units",86bf966e9795896610e0d4609ad4b2ca489e3438,2388079,0,0,43,1398650723,0
Paper,"Why Does Unsupervised Pre-training Help Deep Learning?",c03f42edc1ceb9f0d4a4fd259ef1ef0803aec192,1291944,2,0,114,1398650723,0
Paper,"A Model of the Perception of Facial Expressions of Emotion by Humans: Research Overview and Perspectives",0640d358d4e297c0ad855d874d554d83fd5606b4,1679269,2,0,95,1398650723,0
Paper,"Stability of Density-Based Clustering",fdce3a5899f58bdae0f8a06105576ddc81eb89e1,2207175,0,0,31,1398650723,0
Paper,"Regularized Principal Manifolds (Kernel Machines Section)",54fde50d7ead3bddc030d1b3c9348d89e698a1d2,728955,0,0,32,1398650723,0
Paper,"Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization",fce657527452309b8424f8064c66ffe171d3c851,2908147,0,0,38,1398650724,0
Paper,"Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers",1b022ef4ae73fcab4ec419909171e8b337615d0d,649077,0,0,49,1398650724,0
Paper,"FastInf: An Efficient Approximate Inference Library",0d6ae43319679a7f2d46371b04e21d1a6b18595c,32598,0,0,43,1398650724,0
Paper,"Learning Instance-Specific Predictive Models",6d053654c5ef917bfa57f520a9960678b0bf87d4,474953,0,0,40,1398650724,0
Paper,"Probability Product Kernels (Special Topic on Learning Theory)",99298a049a113961f3b4cba160ea30c73091c312,742632,0,0,50,1398650724,0
Paper,"Fast Approximation of Matrix Coherence and Statistical Leverage",20cb8b1f84a0405538ca7ea30ce8618f749ccef2,285257,0,0,29,1398650724,0
Paper,"Introduction to the Special Issue on Machine Learning Methods for Text and Images",69af795cc5dd6387b7561fd20ff72615d802bb28,346302,0,0,55,1398650724,0
Paper,"Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains",f1ecf4fae4c705c7db6c7731b896c1f896f58d41,256291,0,0,39,1398650724,0
Paper,"A Geometric Approach to Multi-Criterion Reinforcement Learning",8dee57dd28d7a62ee2e35c68a9b8f04be69bcc69,309350,0,0,58,1398650724,0
Paper,"Restricted Eigenvalue Properties for Correlated Gaussian Designs",674c1f85278061a46d1a4a61a5234983c2abdbcc,153447,0,0,32,1398650724,0
Paper,"Blind Source Recovery: A Framework in the State Space",c4f729a7185a1a420bfe12f21db64289345a26d3,196763,0,0,36,1398650724,0
Paper,"Algorithmic Luckiness",d71eaafbc22e4c039467db80d9c031f54e390627,414671,0,0,38,1398650724,0
Paper,"Learning with Mixtures of Trees",d2a046b69cc0f8f04a443f01f6b495e220b05b75,347232,0,0,29,1398650724,0
Paper,"A Comparison of the Lasso and Marginal Regression",b6126eb63713f8560bdf000c55e06e9b70570039,953292,0,0,39,1398650724,0
Paper,"Algebraic Geometric Comparison of Probability Distributions",a8ed169e525254fe11d75b824f2d1ba95b9e9643,534833,0,0,40,1398650724,0
Paper,"On Spectral Learning",c3967c3de128b6bfa1800879d4378495b0bc4032,152333,0,0,31,1398650725,0
Paper,"Semi-Supervised Novelty Detection",9fdd1dd5190e1360c2173cab897ebfc26480e3dd,291502,0,0,31,1398650725,0
Paper,"Metric and Kernel Learning Using a Linear Transformation",5dec4c22172cf72a9ecf73b43d563e969ba40ed7,473906,0,0,36,1398650725,0
Paper,"Consistent Model Selection Criteria on High Dimensions",f1f26d26cf9b7646221ac32cfd431bd9acf54cde,147586,0,0,32,1398650726,0
Paper,"Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning",b0da46a4d6018f022b5e22af6cd2b546e2d7aca4,324360,0,0,31,1398650726,0
Paper,"Sampling Methods for the Nystrm Method",be9f7827c593f14f5d2cdb28d395d90e867a29b4,210917,0,0,29,1398650726,0
Paper,"Computable Shell Decomposition Bounds",3f04847ac68a3ce462ee82f5d06e8147c88f3ea0,226901,0,0,36,1398650726,0
Paper,"Learning Non-Stationary Dynamic Bayesian Networks",657a539d78ca85231a4c30b7779e7f777d3e00ac,1875815,0,0,40,1398650726,0
Paper,"Posterior Regularization for Structured Latent Variable Models",2b305b61748592f3960e5164c7a75e679acc48a3,1181939,0,0,33,1398650726,0
Paper,"Learning Algorithms for the Classification Restricted Boltzmann Machine",7111107e9b410dcb938243037b1c2cab411ae0d0,369756,0,0,34,1398650726,0
Paper,"Coherence Functions with Applications in Large-Margin Classification Methods",ee7e4e81f3992cbd660a706564c90dfbe7600ed1,345578,0,0,28,1398650726,0
Paper,"Distributional Scaling: An Algorithm for Structure-Preserving Embedding of Metric and Nonmetric Spaces",412dfcfddc78602cb2c06cf7eed5024caacceb39,563080,0,0,39,1398650727,0
Paper,"Bundle Methods for Regularized Risk Minimization",50af39c04117a844d8f46ac37602d26955d8702a,1836816,0,0,36,1398650727,0
Paper,"High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency",274969581d5f4d221b266d6c6b67acbfc491762c,205180,0,0,42,1398650727,0
Paper,"A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification",e0342574371245947e145f49125d247966c42c76,6473660,0,0,38,1398650727,0
Paper,"Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees",16e0cd092149a1d0d886146f917b411ee9bfe623,129905,0,0,35,1398650727,0
Paper,"Selective Sampling and Active Learning from Single and Multiple Teachers",fb08d84af039c318a50f8406cd679ad90ba2d758,364201,0,0,36,1398650727,0
Paper,"Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance",338e2e4bc75b07104e73e11440ca633eb144ce7b,240549,0,0,33,1398650727,0
Paper,"Learning Bounded Treewidth Bayesian Networks",5ef14ebb31914e28d839ce14a842d455fcdd6a30,3179328,0,0,41,1398650727,0
Paper,"Evidence Contrary to the Statistical View of Boosting",bd0aa8d48ad8b8e504f2a6f961d747743a597919,973130,0,0,38,1398650728,0
Paper,"Approximate Tree Kernels",33c558a7bdaca3d68c9009a4789c23c370f54d4b,373352,0,0,32,1398650728,0
Paper,"Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity",ce87912ab6bf6bf6898f95309f0a21564a85091e,502646,0,0,33,1398650728,0
Paper,"Tree Induction vs. Logistic Regression: A Learning-Curve Analysis",56e25fd7bb45197ace4a3cb3f6493878d1076924,309924,0,0,44,1398650728,0
Paper,"Bayesian Mixed-Effects Inference on Classification Performance in Hierarchical Data Sets",2e4f939686b1ee3662c375137ee2500d51308deb,1695411,0,0,49,1398650728,0
Paper,"Online Learning in the Embedded Manifold of Low-rank Matrices",6e74f34f9f7d264c65c7c5abab71bde6dfe3596a,337098,0,0,44,1398650728,0
Paper,"Active Learning via Perfect Selective Classification",4df9c8a69217a388ad08e131f9f3135d1bfa0678,194656,0,0,40,1398650728,0
Paper,"On Online Learning of Decision Lists",a6b41b30aaeebe94acc7ed4f4fa59f11f8fc8653,523749,0,0,36,1398650728,0
Paper,"Variable Selection in High-dimensional Varying-coefficient Models with Global Optimality",76cf546bf74aa2b8fac63cd4d8fa28b32a2db40f,256723,0,0,36,1398650728,0
Paper,"Expectation Truncation and the Benefits of Preselection In Training Generative Models",a7b797f1c372cb39ec23fd49fca4a82bf0e204ad,1438325,0,0,39,1398650729,0
Paper,"New Techniques for Disambiguation in Natural Language and Their Application to Biological Text",03476ad6223764d02fd63fc63e999d3c021b2840,274564,0,0,56,1398650729,0
Paper,"Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms",00d5583c3d2cef10043727f3fe893ee0d7da8591,486620,0,0,49,1398650729,0
Paper,"Using Contextual Representations to Efficiently Learn Context-Free Languages",3855a22689cf7ff8aa35e59fae1a7dd36fc6943f,356131,0,0,33,1398650729,0
Paper,"Sparse Semi-supervised Learning Using Conjugate Functions",cddb9ae68147ba451d549738f0bfef2786237486,331420,0,0,35,1398650729,0
Paper,"An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons",94ce5e5953a7438ff6e792ff93f22aef1ce1c02f,343897,0,0,41,1398650729,0
Paper,"Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training",dd455fdfb4bc66e32547d59dba4e95ef01bac8aa,304579,0,0,34,1398650729,0
Paper,"Task Clustering and Gating for Bayesian Multitask Learning",6120c5133b7aa90e32951c74015d5edbc450788e,285467,0,0,50,1398650729,0
Paper,"A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation",1a66f047252e0beb2526052b1ec34ec4a291dc03,2338783,0,0,44,1398650729,0
Paper,"An Efficient Explanation of Individual Classifications using Game Theory",3397ba9d22c9d32db2a34cb7f54cd42af8d81594,690800,0,0,67,1398650729,0
Paper,"A Recursive Method for Structural Learning of Directed Acyclic Graphs",1639f8f3024d3007cb73b229cfea66fa561e3f2e,986243,0,0,44,1398650729,0
Paper,"Refinement of Operator-valued Reproducing Kernels",b509b5ce4211a0131fa8473ce008b9820b40763a,458860,0,0,34,1398650729,0
Paper,"Large-scale Linear Support Vector Regression",b8af5361e7ddba127c6c19c56e49b8b4257b5c37,1080182,0,0,39,1398650730,0
Paper,"A Geometric Approach to Sample Compression",83a478eded8871fdc9b9f5d6f04c3e62345d6250,501023,2,0,50,1398650730,0
Paper,"A Topic Modeling Toolbox Using Belief Propagation",9e9911232d0f2f7d5a4b87b1faa2411107786266,61471,0,0,38,1398650730,0
Paper,"A Generalized Path Integral Control Approach to Reinforcement Learning",0142723bea471e43f141538dacf4ed809e1756c6,1090353,0,0,42,1398650730,0
Paper,"Word-Sequence Kernels",dfd1871e922ff4c2811882e3d719ea425cd189aa,13792,0,0,40,1398650730,0
Paper,"Characterization, Stability and Convergence of Hierarchical Clustering Methods",043cafaa559a5088f491fd6d29acadef767d252f,857225,0,0,39,1398650730,0
Paper,"Image Denoising with Kernels Based on Natural Image Relations",722798b9b0b8e12eec206ac3bf2844bceb6ab60f,1767344,2,0,52,1398650730,0
Paper,"Bouligand Derivatives and Robustness of Support Vector Machines for Regression",6716583910ceedf4985d3f1fd4e5fb6b8f53a242,531564,0,0,44,1398650731,0
Paper,"GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression",41860ce928ae47eb50b7dcd8170871277d2e1efa,43282,0,0,35,1398650731,0
Paper,"Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions",644188fbca51acc28a99ef5c6b5fc18e147e30e7,1937936,0,0,34,1398650731,0
Paper,"Bayes Point Machines (Kernel Machines Section)",d1d353fe6c9e316ef89dc78a499bba2d2b7bb4ec,977426,0,0,36,1398650731,0
Paper,"Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data",f0c816214fba191eb864acb4bc1139920972b00b,1088886,0,0,34,1398650731,0
Paper,"Graph Kernels",902c20ad640a17526110f45a87456118562f8fbb,1564895,0,0,43,1398650731,0
Paper,"Mixability is Bayes Risk Curvature Relative to Log Loss",aa86dcd4f400d55d2bbf9b3fe3c2ca5d3c177703,429797,0,0,39,1398650732,0
Paper,"Consistent Nonparametric Tests of Independence",124c06f5f90001f63019dd5b2047d275a34bfc95,369959,0,0,37,1398650732,0
Paper,"Probability Estimates for Multi-class Classification by Pairwise Coupling",07087e767df537c2df206dddb799d20abd627c22,501956,0,0,41,1398650732,0
Paper,"Pattern for Python",fde4c9025c1cdba3606c63f5a70bc313c71d46a0,94192,4,0,232,1398650732,0
Paper,"Linear Fitted-Q Iteration with Multiple Reward Functions",ab524298f818565f7b4d711895cc9f68cd2d442b,1296091,0,0,31,1398650732,0
Paper,"Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso",83e025f04f12b8ede210a6e6de649563257bcd85,911768,0,0,36,1398650732,0
Paper,"On Nearest-Neighbor Error-Correcting Output Codes with Application to All-Pairs Multiclass Support Vector Machines",0d0217867c557ff185fc893b6cf9b460c3580724,161921,0,0,39,1398650732,0
Paper,"Topology Selection in Graphical Models of Autoregressive Processes",74af429ea8a9a70fc6e8628c967415b6b92b5084,324793,0,0,33,1398650732,0
Paper,"Preference Elicitation and Query Learning (Special Topic on Learning Theory)",1101a44824c650a0db007a929a626d81cdfcf5c6,208635,0,0,42,1398650732,0
Paper,"Regularized Bundle Methods for Convex and Non-Convex Risks",bbca1f9f0daac4327e0c4f6ad9e889b2b11fa6a9,576405,0,0,34,1398650732,0
Paper,"Path Kernels and Multiplicative Updates",fe0610492c0ceb4f4013b0c95c7f349cec766f68,131870,0,0,25,1398650733,0
Paper,"Max-margin Classification of Data with Absent Features",10f362e8e840da581437cea0f6cbcbbc430d2887,292242,0,0,38,1398650733,0
Paper,"Fast and Scalable Local Kernel Machines",058438dc9c8f680864afbb8953e005c92f8da308,425905,0,0,57,1398650733,0
Paper,"Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers",9886fcb86453efd5dd63496426ac3ce46ac5a5dd,277919,0,0,41,1398650733,0
Paper,"Exact Bayesian Structure Discovery in Bayesian Networks",24381f608b09bb20958184f73c895baf16522f47,173898,0,0,42,1398650733,0
Paper,"Iterative Reweighted Algorithms for Matrix Rank Minimization",24dbb7a0e4123b4b6782d4c2c8bcce583de40ff0,335721,0,0,40,1398650733,0
Paper,"Classification Using Geometric Level Sets",5237e8c321f52ece1a04f5e377b4c07d5ce85489,1036107,0,0,36,1398650733,0
Paper,"Stability Bounds for Stationary -mixing and -mixing Processes",dae7382244d21381a9a098efe009838ec491862b,207792,0,0,34,1398650734,0
Paper,"Sparse Spectrum Gaussian Process Regression",510a89459197e881352e8a99ccea659083c3f96d,178388,0,0,37,1398650734,0
Paper,"Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation",2a0497807adea125d3c68cdc6a9c5e96473e8596,918894,0,0,40,1398650734,0
Paper,"Least-Squares Policy Iteration",2f194659087417e235adbaf606c9e170b7b6002c,312970,0,0,42,1398650734,0
Paper,"Random Search for Hyper-Parameter Optimization",57622727b8c7413fba521f635ade9ef36223023c,728274,0,0,39,1398650734,0
Paper,"A Family of Additive Online Algorithms for Category Ranking",f70052bb09cf26851208fc7b73d4dc8a5b710861,417996,0,0,36,1398650734,0
Paper,"Smoothing Multivariate Performance Measures",821f225940a7aed9f6d38367cd54684bbd0f25a6,858607,0,0,31,1398650735,0
Paper,"Concentration Inequalities for the Missing Mass and for Histogram Rule Error",584127b9189720f45039750333be5e5625a9c1ce,323711,0,0,32,1398650735,0
Paper,"On the Importance of Small Coordinate Projections",75c3a5eaf6b12fd9a7b08a4e10d6ec784af30ae6,215553,0,0,33,1398650735,0
Paper,"A Multiscale Framework For Blind Separation of Linearly Mixed Signals",d63cbc0620adcf668aebd2f0274e9e8c2bc0a5d9,3357313,0,0,35,1398650735,0
Paper,"On the Rate of Convergence of the Bagged Nearest Neighbor Estimate",8e2157d9ced05bfd778af368695c050027f37038,193656,0,0,35,1398650735,0
Paper,"The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem",03262bd503378b1d0c274a01d4022ad0ecb2de1d,926725,0,0,59,1398650735,0
Paper,"Reinforcement Learning with Factored States and Actions",6776a581124c86f12e3aca0c4629f9e71adc45d6,210671,0,0,36,1398650735,0
Paper,"Regret Bounds and Minimax Policies under Partial Monitoring",2113a0005716fde62b1201c4a2c846a615b30b66,386699,0,0,32,1398650735,0
Paper,"Generalization from Observed to Unobserved Features by Clustering",e4d102e59cf6e3c68d0493b66b3c1ad809b11da3,133378,0,0,28,1398650735,0
Paper,"A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning",81d30aec29d668644d9c0b4e64bc41bdefa2d929,1319467,0,0,48,1398650735,0
Paper,"Algorithms for Learning Kernels Based on Centered Alignment",174f90e3b63899aa00e90012bd3e44ee5b79efb6,266595,0,0,43,1398650735,0
Paper,"Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks",a9c761b751ed6ffbc5058ce97d767441844aaa08,449191,0,0,58,1398650736,0
Paper,"Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies",87f561d3d72af9b20f9d0298efddb88f948591db,43186,0,0,62,1398650736,0
Paper,"Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data",bc809547166bcf9d0fb0bcb7b277ddaccf7c4f69,682234,0,0,54,1398650736,0
Paper,"Preference Elicitation via Theory Refinement",d0c45984badd217ca59844462573dc5edec9574b,164756,0,0,29,1398650736,0
Paper,"The Representational Power of Discrete Bayesian Networks",937e6389c6ace73d55931e39e9ae1e3d1ac6e72c,457485,0,0,42,1398650736,0
Paper,"Transfer in Reinforcement Learning via Shared Features",ad7c56096190d25cd8e362b9a89e4b289b46c3b8,434223,1,0,39,1398650736,0
Paper,"PAC-Bayes Bounds with Data Dependent Priors",13efa078bace9fe68035ee3da1f60e4b3270e1e3,325019,0,0,39,1398650736,0
Paper,"Limitations of Learning Via Embeddings in Euclidean Half Spaces",fd6c5f091409009d84c12d68d4dcc1f272a2ac95,283793,0,0,33,1398650736,0
Paper,"A Convergent Online Single Time Scale Actor Critic Algorithm",2d26acfe408e70b3c26efacea54735088bf82c65,325612,0,0,41,1398650737,0
Paper,"Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels",0d23c6099604e45283962057800a6e42f6384b2d,642663,0,0,66,1398650737,0
Paper,"Boosting as a Regularized Path to a Maximum Margin Classifier",6bf88072c9021e637a8a624e79c15e70961ede1e,1262309,0,0,40,1398650737,0
Paper,"Support Vector Machine Soft Margin Classifiers: Error Analysis",aa95f64966993e878db72d2cc3aecaf1d475716b,2700586,0,0,48,1398650737,0
Paper,"Energy-Based Models for Sparse Overcomplete Representations",4108bc464fce4a222c2e26396eb6a628259044d3,218010,0,0,32,1398650737,0
Paper,"Sufficient Dimensionality Reduction (Kernel Machines Section)",8663822d38c2e62dfc0bc063e839688ba68088ed,195344,0,0,36,1398650737,0
Paper,"FINkNN: A Fuzzy Interval Number k-Nearest Neighbor Classifier for Prediction of Sugar Production from Populations of Samples",502de11e8c7df6ccbf8b37f8d1a1b516a2cd577d,360764,0,0,42,1398650737,0
Paper,"Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting",732e7896b2fdd062e94a459d6ba4f62ced4c7f29,662375,0,0,43,1398650737,0
Paper,"PAC-Bayesian Analysis of Co-clustering and Beyond",449b5b080eb4f043034dc16497d31ee95b97acf7,614956,0,0,37,1398650737,0
Paper,"Confidence-Weighted Linear Classification for Text Categorization",0d19898b3e3b4293787d1e7b210062161986be93,2042450,1,0,43,1398650737,0
Paper,"Hit Miss Networks with Applications to Instance Selection",756bb7c2680231279d573ed63f0b1e24da2cea57,195861,0,0,34,1398650738,0
Paper,"Lp-Nested Symmetric Distributions",7f313160e766098db344b1656e2ed8789c49c69a,3369257,0,0,33,1398650738,0
Paper,"ILP: A Short Look Back and a Longer Look Forward",9ed45b61015c6141c2852e0cc4f63b978ee6f7eb,11597,0,0,34,1398650738,0
Paper,"Inducing Tree-Substitution Grammars",0f7ed39fca9f78a55a6902e64890856b66fcb5e4,1118269,0,0,45,1398650738,0
Paper,"Linear Algorithms for Online Multitask Classification",e90de45a88ab4dc26492b4489f438d890281a288,402565,0,0,32,1398650738,0
Paper,"Composite Binary Losses",ae3c57eec19b8e3217fef758e20b4461cda5bc0c,706127,0,0,33,1398650739,0
Paper,"On-Line Sequential Bin Packing",0495f04d838b46686431fd619f3e215bceaa2788,166101,0,0,36,1398650739,0
Paper,"Quantum Set Intersection and its Application to Associative Memory",34a70fa34c879bf42656631c32a7712e99dcd028,404248,0,0,42,1398650739,0
Paper,"Model-based Boosting 2.0",3cce95f965195c957591a4127581ae75070ec855,103265,2,0,42,1398650739,0
Paper,"Covariance in Unsupervised Learning of Probabilistic Grammars",6d65bd5ba3f10d7dd7759758cb94dbfd4b3e8677,383374,0,0,35,1398650739,0
Paper,"On the Rate of Convergence of Regularized Boosting Classifiers",6df40c5b34af78337350e58acf68b7996400ca1e,198893,0,0,31,1398650740,0
Paper,"Ultraconservative Online Algorithms for Multiclass Problems",2ea5a07cb4d042f1e177715b5104d8a4b3d78332,6696501,0,0,41,1398650740,0
Paper,"Nash Q-Learning for General-Sum Stochastic Games",4e78d4676e3609d7748288f77ae9a4df5732766f,780696,0,0,42,1398650740,0
Paper,"R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning",3699dda91f82f2c6083f50166e3675779762ee93,101231,0,0,41,1398650740,0
Paper,"Security Analysis of Online Centroid Anomaly Detection",d3d9e74feb33847b8965f7c7a7e2fa0f2c30cfde,912389,6,0,97,1398650740,0
Paper,"Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials",e88fe7bda5fbabd26c7bbcb05a2c133bc54a789d,465776,0,0,31,1398650740,0
Paper,"Exploration in Relational Domains for Model-based Reinforcement Learning",a13eed285b9f81acac1a8cbb4bedf91ce1524b76,697869,0,0,36,1398650740,0
Paper,"Online Choice of Active Learning Algorithms",8884920c4f634ffb624b921eb9046dfaecacf6b1,518473,0,0,68,1398650740,0
Paper,"Algorithms for Sparse Linear Classifiers in the Massive Data Setting",a2a44d367d849fd323b3da394f52b1b4bbd38ae9,386096,0,0,45,1398650740,0
Paper,"Sally: A Tool for Embedding Strings in Vector Spaces",acef731ff2e0ed888e7f860cb27c1417866c4f95,413354,0,0,37,1398650741,0
Paper,"Rational Kernels: Theory and Algorithms (Special Topic on Learning Theory)",64aacc7f046be66cfcc98e2c684bc5aa1c97d7ca,322046,0,0,43,1398650741,0
Paper,"A Robust Minimax Approach to Classification",bff8467895bf3ea2712ace7d87efb7a5f85b560b,523763,0,0,42,1398650741,0
Paper,"No Unbiased Estimator of the Variance of K-Fold Cross-Validation",cb8c8a3f743a330e249ef360ba6fa2147f4702ba,214685,0,0,40,1398650741,0
Paper,"Knowledge-Based Kernel Approximation",501e017a78ab24b0063bd041f675af7675689b20,152553,0,0,45,1398650741,0
Paper,"Regularized Discriminant Analysis, Ridge Regression and Beyond",e237f7aaaa9cd93a68b3abe3583c1bb75dcaad3d,332200,0,0,41,1398650741,0
Paper,"Comments on the Complete Characterization of a Family of Solutions to a Generalized Fisher Criterion",5aa0104d675b610e87a5b845a03140ea4657cc0d,439537,0,0,40,1398650741,0
Paper,"Pairwise Support Vector Machines and their Application to Large Scale Problems",d058dbfcc0abbcc7ea60eb1696f2d463f692a241,262888,0,0,40,1398650742,0
Paper,"Lyapunov Design for Safe Reinforcement Learning",622c9de43b3ce42daa46a9622e36d3e5bb2c1a21,1127186,0,0,45,1398650742,0
Paper,"Approximations for Binary Gaussian Process Classification",23b7baf9db5d41de8f1f5f57e25f97c26a2637e6,62856,0,0,38,1398650742,0
Paper,"Minimax Manifold Estimation",5a779dec342b3228270697565c01547007ba131a,2325836,0,0,44,1398650743,0
Paper,"A Neural Probabilistic Language Model",ccdfe60f5bb75ca85473c90d483e3802d53f5d12,242236,0,0,86,1398650743,0
Paper,"Lagrangian Support Vector Machines (Kernel Machines Section)",50df310af8d5acc4986cafae0cd716decb2c0592,280392,0,0,68,1398650743,0
Paper,"Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise",d1c93e3859c2d0f6cc9a7e4ad1a6a04c28f2d5c9,280196,0,0,35,1398650744,0
Paper,"Erratum: SGDQN is Less Careful than Expected",5ae1c9c1b06c251c154efefee93dcb23539d914e,998426,0,0,39,1398650744,0
Paper,"Extensions to Metric-Based Model Selection",93a55ffbc30b6cfefaa4b665e979717e99d4405e,657989,0,0,40,1398650783,0
Paper,"A Kernel Two-Sample Test",234705eaac998d5c04b8e4c8a096c120d66404a0,479876,0,0,157,1398650785,0
Paper,"On the Necessity of Irrelevant Variables",ffa02bdccbfd01ac5ce35c2bfee6210abb4ddd0f,299759,0,0,33,1398650785,0
Paper,"A Local Spectral Method for Graphs: With Applications to Improving Graph Partitions and Exploring Data Graphs Locally",5a0a7c5620fb0a6525dd940cff562869c737a978,968869,0,0,50,1398650785,0
Paper,"On the Equivalence of Linear Dimensionality-Reducing Transformations",709afa4fc8581b99cd6f0991f6f660786f2326a3,336137,0,0,34,1398650787,0
Paper,"Multi-Assignment Clustering for Boolean Data",df72006546f40f6fc8313fdec7dd4e10d4b913c1,604577,0,0,35,1398650787,0
Paper,"Model Averaging for Prediction with Discrete Bayesian Networks",65a8c28e71972ecba5d24fd655b627f1b2423960,251423,0,0,49,1398650789,0
Paper,"A Unified View of Performance Metrics: Translating Threshold Choice into Expected Classification Loss",dc07b26f8acd99dfc7d1763d46079930a1d1b4c5,563388,0,0,49,1398650794,0
Paper,"Statistical Dynamics of On-line Independent Component Analysis",3b1322671d42bb6e951a700fad288137dcaefece,1016257,0,0,46,1398650794,0
Paper,"Latent Dirichlet Allocation",886506949d35110e5cfcf1cd5c5ffb16e0dc904b,388437,0,0,43,1398650794,0
Paper,"Learning Semantic Lexicons from a Part-of-Speech and Semantically Tagged Corpus Using Inductive Logic Programming",dd06605483247bc97dfdf2a688627f9552792557,533074,0,0,66,1398650795,0
Paper,"A Compression Approach to Support Vector Model Selection",88785a8c94e9ffa4fca127ae27f7a5109eb3648b,1358264,1,0,77,1398650796,0
Paper,"Special Issue on the Eighteenth International Conference on Machine Learning (ICML2001)",818692398ce10db04c3c86df13a5732212f65ef9,443405,0,0,38,1398650796,0
Paper,"Continuous Time Bayesian Network Reasoning and Learning Engine",bfda57d28a4b8a0370bcc80bf096f64c08b6c3b6,34130,0,0,51,1398650796,0
Paper,"Finding Recurrent Patterns from Continuous Sign Language Sentences for Automated Extraction of Signs",b37898e31c5ac61100e878ce252025c023470ad5,982838,0,0,44,1398650797,0
Paper,"Introduction to Special Issue on Independent Components Analysis",57337b3b7e9018a8f640c5033bd6c77d238b03e8,259595,0,0,45,1398650797,0
Paper,"Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming",77750329f24c8f314dd436be7b00bd6ec370ff2f,316400,2,0,54,1398650799,0
Paper,"Local and Global Scaling Reduce Hubs in Space",4308fad66470491613d8e4886126fd2482090480,388422,0,0,54,1398650799,0
Paper,"On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation",1fb1a2623f50c709710e610877d665ca1933fe01,759286,0,0,48,1398650800,0
Paper,"Entropy Search for Information-Efficient Global Optimization",b05a6f20298620c47565f3a219372c7365d68fcb,891099,0,0,47,1398650800,0
Paper,"Learnability, Stability and Uniform Convergence",3fa89ca74baca9a6183c78adcea426cc3f4bf3ef,331233,0,0,44,1398650801,0
Paper,"Using Markov Blankets for Causal Structure Learning(Special Topic on Causality)",8e08ddb27ae589a238417b68e587dcb48350055b,506990,0,0,53,1398650801,0
Paper,"Facilitating Score and Causal Inference Trees for Large Observational Studies",0ee5b8cf1a70ba71aba9c80006ac5f2bb93ad498,355273,0,0,46,1398650802,0
Paper,"Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels",78694e1b7d119bf3f90c774a9d64c7397561fb05,231505,2,0,130,1398650802,0
Paper,"Learning Evaluation Functions to Improve Optimization by Local Search",1192c9b53b9b8e9d0770920ed80fbb079ac3996d,568358,0,0,63,1398650805,0
Paper,"Designing Committees of Models through Deliberate Weighting of Data Points",234ab9d3e095f06f64a92ec1116b569e823463e8,237348,0,0,45,1398650806,0
Paper,"Importance Sampling for Continuous Time Bayesian Networks",1667047cab708a174b089171bfaa40245bd7f83b,246974,0,0,54,1398650810,0
Paper,"Shark(Machine Learning Open Source Software Paper)",0b19f22d3cd0e9736fa1c8da332e083432c265e9,503857,1,0,129,1398650810,0
Paper,"PREA: Personalized Recommendation Algorithms Toolkit",20c5722a541aa1ba00308b29f32edddbf8d99f28,290788,0,0,73,1398650817,0
Paper,"Feature Selection via Dependence Maximization",cf7bf7de805b2266ded5349020a94a6670341096,1553412,0,0,66,1398650817,0
Paper,"Lossless Online Bayesian Bagging",3505ee186a69f85a659c187209e896c10ee5af83,383895,2,0,64,1398651002,0
Paper,"Learning Probabilistic Models: An Expected Utility Maximization Approach",932f340dabe2e3416e210b9b62bfdb8bf6d7ffa3,271695,0,0,94,1398651003,0