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Alexander Rakhlin

Affiliations: 
University of California, Berkeley, Berkeley, CA, United States 
Area:
Machine Learning, Online Learning / Expert Advice, Optimization, Statistical Learning Theory, Multitask Learning, Generalization Bounds,
Website:
http://www.eecs.berkeley.edu/%7Erakhlin/
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"Alexander Rakhlin"
Bio:

Alexander Rakhlin is currently a postdoc at UC Berkeley, working with Peter Bartlett. He completed his PhD at the Center for Biological and Computational Learning, MIT. Dr. Rakhlin will be moving to UPenn in December 2008.

Mean distance: 13.99 (cluster 29)
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Tomaso A. Poggio grad student 2006 MIT (guest) Delete Edit

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Publications

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Liang T, Rakhlin A. (2020) Just interpolate: Kernel “Ridgeless” regression can generalize Annals of Statistics. 48: 1329-1347
Rakhlin A, Sridharan K, Tsybakov AB. (2017) Empirical entropy, minimax regret and minimax risk Bernoulli. 23: 789-824
Cai TT, Liang T, Rakhlin A. (2017) Computational and statistical boundaries for submatrix localization in a large noisy matrix Annals of Statistics. 45: 1403-1430
Cai TT, Liang T, Rakhlin A. (2016) Geometric inference for general high-dimensional linear inverse problems Annals of Statistics. 44: 1536-1563
Shahrampour S, Rakhlin A, Jadbabaie A. (2016) Distributed Detection: Finite-Time Analysis and Impact of Network Topology Ieee Transactions On Automatic Control. 61: 3256-3268
Bartók G, Foster DP, Pál D, et al. (2014) Partial monitoring - Classification, regret bounds, and algorithms Mathematics of Operations Research. 39: 967-997
Rakhlin A, Sridharan K, Tewari A. (2014) Sequential complexities and uniform martingale laws of large numbers Probability Theory and Related Fields. 1-43
Agarwal A, Foster DP, Hsu D, et al. (2013) Stochastic convex optimization with bandit feedback Siam Journal On Optimization. 23: 213-240
Seshia SA, Rakhlin A. (2012) Quantitative analysis of systems using game-theoretic learning Transactions On Embedded Computing Systems. 11
Abernethy JD, Hazan E, Rakhlin A. (2012) Interior-point methods for full-information and bandit online learning Ieee Transactions On Information Theory. 58: 4164-4175
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