NIPS Proceedings
^{β}
Books
Mikhail Belkin
16 Papers
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
(2018)
Diving into the shallows: a computational perspective on large-scale shallow learning
(2017)
Clustering with Bregman Divergences: an Asymptotic Analysis
(2016)
Graphons, mergeons, and so on!
(2016)
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA
(2015)
Learning with Fredholm Kernels
(2014)
Fast Algorithms for Gaussian Noise Invariant Independent Component Analysis
(2013)
Inverse Density as an Inverse Problem: the Fredholm Equation Approach
(2013)
Data Skeletonization via Reeb Graphs
(2011)
Semi-supervised Learning using Sparse Eigenfunction Bases
(2009)
The Value of Labeled and Unlabeled Examples when the Model is Imperfect
(2007)
Convergence of Laplacian Eigenmaps
(2006)
On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts
(2006)
Limits of Spectral Clustering
(2004)
Using Manifold Stucture for Partially Labeled Classification
(2002)
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
(2001)