Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples.pdf	416.15kB

Type: Paper

Tags:

Metadata:

@article{7:85,author={Mikhail Belkin and Partha Niyogi and Vikas Sindhwani}, Title={Manifold  Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples},journal={Journal of Machine Learning Research},volume={7}, url={http://www.jmlr.org/papers/volume7/belkin06a/belkin06a.pdf}}

Citation:

Niyogi, P., Belkin, M., & Sindhwani, V.. (2014). Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples [Data set]. Academic Torrents. https://academictorrents.com/details/f3a3b1a97bd8fdb762685f05318b822e295fa059

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples Partha Niyogi and Mikhail Belkin and Vikas Sindhwani

Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
Partha Niyogi and Mikhail Belkin and Vikas Sindhwani