Mikhail Belkin
49 papers · 2006–2025 · 10 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 17 separate collaboration groups - the largest holds only 35% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Mikhail Belkin?
5 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Yusu Wang, Qichao Que, Justin Eldridge
9 papers
· 2011–2018
· NeurIPS, AISTATS, COLT
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Unperturbed: spectral analysis beyond Davis-Kahan
ALT 2018
Back to the Future: Radial Basis Function Networks Revisited
AISTATS 2016
Graphons, mergeons, and so on!
NeurIPS 2016
Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clustering
COLT 2015
Learning with Fredholm Kernels
NeurIPS 2014
Inverse Density as an Inverse Problem: the Fredholm Equation Approach
NeurIPS 2013
Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries
COLT 2012
Data Skeletonization via Reeb Graphs
NeurIPS 2011
Semi-supervised Learning by Higher Order Regularization
AISTATS 2011
12 papers whose co-authors appear nowhere else under this name
A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis
COLT 2025
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
ICLR 2024
Classification vs regression in overparameterized regimes: Does the loss function matter?
JMLR 2021
Conference on Learning Theory 2021: Post-conference Preface
COLT 2021
Multiple Descent: Design Your Own Generalization Curve
NeurIPS 2021
Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures
NeurIPS 2021
Does data interpolation contradict statistical optimality?
AISTATS 2019
Approximation beats concentration? An approximation view on inference with smooth radial kernels
COLT 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
NeurIPS 2018
Learning privately from multiparty data
ICML 2016
Laplacian Support Vector Machines Trained in the Primal
JMLR 2011
On Learning with Integral Operators
JMLR 2010