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20092024
most citedTheory of Deep Learning IIb: Optimization Properties of SGD

44 citations · 143 across the 23 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.LG201911 cited

Vector Contraction for Rademacher Complexity

Dylan J. Foster, Alexander Rakhlin

We show that the Rademacher complexity of any -valued function class composed with an -Lipschitz function is bounded by the maximum Rademacher comple…

eess.SY2019

Data Driven Estimation of Stochastic Switched Linear Systems of Unknown Order

Tuhin Sarkar, Alexander Rakhlin, Munther A. Dahleh

We address the problem of learning the parameters of a mean square stable switched linear systems (SLS) with unknown latent space dimension, or \textit{order}, from its noisy input…

math.ST2019

On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels

Tengyuan Liang, Alexander Rakhlin, Xiyu Zhai

We study the risk of minimum-norm interpolants of data in Reproducing Kernel Hilbert Spaces. Our upper bounds on the risk are of a multiple-descent shape for the various scalings o…

eess.IV2019

Breast Tumor Cellularity Assessment using Deep Neural Networks

Alexander Rakhlin, Aleksei Tiulpin, Alexey A. Shvets +3

Breast cancer is one of the main causes of death worldwide. Histopathological cellularity assessment of residual tumors in post-surgical tissues is used to analyze a tumor's respon…

math.ST2019

Optimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression

Gil Kur, Yuval Dagan, Alexander Rakhlin

In this paper, we study two problems: (1) estimation of a -dimensional log-concave distribution and (2) bounded multivariate convex regression with random design with an underly…