Yeshwanth Cherapanamjeri | DeepAI

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∙ 05/27/2023

An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification

Pre-trained transformer models have demonstrated success across many nat...

0 Aliyah R. Hsu, 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. ∙

∙ 04/14/2023

Robust Algorithms on Adaptive Inputs from Bounded Adversaries

We study dynamic algorithms robust to adaptive input generated from sour...

0 Yeshwanth Cherapanamjeri, 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. ∙

∙ 11/18/2022

Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time

We study fundamental problems in linear algebra, such as finding a maxim...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 05/06/2022

What Makes A Good Fisherman? Linear Regression under Self-Selection Bias

In the classical setting of self-selection, the goal is to learn k model...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 05/04/2022

Estimation of Standard Auction Models

We provide efficient estimation methods for first- and second-price auct...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 03/03/2022

Uniform Approximations for Randomized Hadamard Transforms with Applications

Randomized Hadamard Transforms (RHTs) have emerged as a computationally ...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 10/17/2021

Terminal Embeddings in Sublinear Time

Recently (Elkin, Filtser, Neiman 2017) introduced the concept of a termi...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 06/23/2021

Adversarial Examples in Multi-Layer Random ReLU Networks

We consider the phenomenon of adversarial examples in ReLU networks with...

12 Peter L. Bartlett, et al. ∙

∙ 04/08/2021

A single gradient step finds adversarial examples on random two-layers neural networks

Daniely and Schacham recently showed that gradient descent finds adversa...

11 Sébastien Bubeck, et al. ∙

∙ 11/24/2020

Optimal Mean Estimation without a Variance

We study the problem of heavy-tailed mean estimation in settings where t...

10 Yeshwanth Cherapanamjeri, et al. ∙

∙ 10/21/2020

On Adaptive Distance Estimation

We provide a static data structure for distance estimation which support...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 07/16/2020

Optimal Robust Linear Regression in Nearly Linear Time

We study the problem of high-dimensional robust linear regression where ...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 05/20/2020

List Decodable Mean Estimation in Nearly Linear Time

Learning from data in the presence of outliers is a fundamental problem ...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 12/23/2019

Algorithms for Heavy-Tailed Statistics: Regression, Covariance Estimation, and Beyond

We study efficient algorithms for linear regression and covariance estim...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 02/06/2019

Testing Markov Chains without Hitting

We study the problem of identity testing of markov chains. In this setti...

0 Yeshwanth Cherapanamjeri, et al. ∙

∙ 02/06/2019

Fast Mean Estimation with Sub-Gaussian Rates

We propose an estimator for the mean of a random vector in R^d that can ...

0 Yeshwanth Cherapanamjeri, et al. ∙

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