Abhishek Shetty | DeepAI

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∙ 09/21/2023

Smooth Nash Equilibria: Algorithms and Complexity

A fundamental shortcoming of the concept of Nash equilibrium is its comp...

0 Constantinos Daskalakis, et al. ∙

∙ 06/22/2023

Adversarial Resilience in Sequential Prediction via Abstention

We study the problem of sequential prediction in the stochastic setting ...

0 Surbhi Goel, et al. ∙

∙ 04/18/2023

Optimal PAC Bounds Without Uniform Convergence

In statistical learning theory, determining the sample complexity of rea...

0 Ishaq Aden-Ali, et al. ∙

∙ 03/08/2023

Smoothed Analysis of Sequential Probability Assignment

We initiate the study of smoothed analysis for the sequential probabilit...

0 Alankrita Bhatt, et al. ∙

∙ 02/20/2023

Progressive Knowledge Distillation: Building Ensembles for Efficient Inference

We study the problem of progressive distillation: Given a large, pre-tra...

0 Don Kurian Dennis, et al. ∙

∙ 12/19/2022

The One-Inclusion Graph Algorithm is not Always Optimal

The one-inclusion graph algorithm of Haussler, Littlestone, and Warmuth ...

0 Ishaq Aden-Ali, et al. ∙

∙ 02/17/2022

Oracle-Efficient Online Learning for Beyond Worst-Case Adversaries

In this paper, we study oracle-efficient algorithms for beyond worst-cas...

0 Nika Haghtalab, et al. ∙

∙ 11/15/2021

Distribution Compression in Near-linear Time

In distribution compression, one aims to accurately summarize a probabil...

0 Abhishek Shetty, et al. ∙

∙ 10/19/2021

Matrix Discrepancy from Quantum Communication

We develop a novel connection between discrepancy minimization and (quan...

0 Samuel B. Hopkins, et al. ∙

∙ 02/16/2021

Smoothed Analysis with Adaptive Adversaries

We prove novel algorithmic guarantees for several online problems in the...

8 Nika Haghtalab, et al. ∙

∙ 08/04/2020

Fractional Pseudorandom Generators from Any Fourier Level

We prove new results on the polarizing random walk framework introduced ...

0 Eshan Chattopadhyay, et al. ∙

∙ 06/17/2020

Smoothed Analysis of Online and Differentially Private Learning

Practical and pervasive needs for robustness and privacy in algorithms h...

9 Nika Haghtalab, et al. ∙

∙ 08/16/2019

Effect of Activation Functions on the Training of Overparametrized Neural Nets

It is well-known that overparametrized neural networks trained using gra...

0 Abhishek Panigrahi, et al. ∙

∙ 07/24/2019

Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature

The Euclidean space notion of convex sets (and functions) generalizes to...

0 Navin Goyal, et al. ∙

∙ 07/13/2018

Non-Gaussian Component Analysis using Entropy Methods

Non-Gaussian component analysis (NGCA) is a problem in multidimensional ...

0 Navin Goyal, et al. ∙

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