Yeshwanth Cherapanamjeri

According to our database1, Yeshwanth Cherapanamjeri authored at least 23 papers between 2017 and 2024.

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Bibliography

2024
Terminal Embeddings in Sublinear Time.
TheoretiCS, 2024

2023
Statistical Barriers to Affine-equivariant Estimation.
CoRR, 2023

An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification.
CoRR, 2023

What Makes a Good Fisherman? Linear Regression under Self-Selection Bias.
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time.
Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Robust Algorithms on Adaptive Inputs from Bounded Adversaries.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Optimal PAC Bounds without Uniform Convergence.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

The One-Inclusion Graph Algorithm is not Always Optimal.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Uniform approximations for Randomized Hadamard Transforms with applications.
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Estimation of Standard Auction Models.
Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

Optimal Mean Estimation without a Variance.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
A single gradient step finds adversarial examples on random two-layers neural networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Examples in Multi-Layer Random ReLU Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Optimal Robust Linear Regression in Nearly Linear Time.
CoRR, 2020

Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond.
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

On Adaptive Distance Estimation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

List Decodable Mean Estimation in Nearly Linear Time.
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

2019
Testing Markov Chains without Hitting.
CoRR, 2019

Fast Mean Estimation with Sub-Gaussian Rates.
Proceedings of the Conference on Learning Theory, 2019

Testing Symmetric Markov Chains Without Hitting.
Proceedings of the Conference on Learning Theory, 2019

2017
Thresholding based Efficient Outlier Robust PCA.
CoRR, 2017

Nearly Optimal Robust Matrix Completion.
Proceedings of the 34th International Conference on Machine Learning, 2017

Thresholding Based Outlier Robust PCA.
Proceedings of the 30th Conference on Learning Theory, 2017


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