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Mikhail Belkin

Professor
Photo of Mikhail Belkin

Biographical Info

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and  applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization.  One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Website: misha.belkin-wang.org

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Angela Yu

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Alex Cloninger

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Yian Ma

Assistant Professor
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Albert Hsiao

Associate Professor
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Janine Tiefenbruck

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Young-Han Kim

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Yusu Wang

Professor
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Lily Weng

Assistant Professor

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Mikhail Belkin

Professor
Photo of Mikhail Belkin

Biographical Info

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and  applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization.  One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Website: misha.belkin-wang.org

Related by Category

Photo of Angela Yu

Angela Yu

Associate Professor
Photo of Alex Cloninger

Alex Cloninger

Assistant Professor 858.534.3992
Photo of Yian Ma

Yian Ma

Assistant Professor
Photo of Albert Hsiao

Albert Hsiao

Associate Professor
Photo of Janine Tiefenbruck

Janine Tiefenbruck

Lecturer
Photo of Young-Han Kim

Young-Han Kim

Professor
Photo of Yusu Wang

Yusu Wang

Professor
Photo of Lily Weng

Lily Weng

Assistant Professor

Communications

Mikhail Belkin

Professor
Photo of Mikhail Belkin

Biographical Info

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and  applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization.  One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Website: misha.belkin-wang.org

Related by Category

Photo of Angela Yu

Angela Yu

Associate Professor
Photo of Alex Cloninger

Alex Cloninger

Assistant Professor 858.534.3992
Photo of Yian Ma

Yian Ma

Assistant Professor
Photo of Albert Hsiao

Albert Hsiao

Associate Professor
Photo of Janine Tiefenbruck

Janine Tiefenbruck

Lecturer
Photo of Young-Han Kim

Young-Han Kim

Professor
Photo of Yusu Wang

Yusu Wang

Professor
Photo of Lily Weng

Lily Weng

Assistant Professor