Thresholding Based Outlier Robust PCA. - Yeshwanth Cherapanamjeri; Prateek Jain 002; Praneeth Netrapalli (COLT, 2017)

Nearly Optimal Robust Matrix Completion. - Yeshwanth Cherapanamjeri; Kartik Gupta; Prateek Jain 002 (ICML, 2017)

Thresholding based Efficient Outlier Robust PCA. - Yeshwanth Cherapanamjeri; Prateek Jain 002; Praneeth Netrapalli (CoRR, 2017)

Testing Symmetric Markov Chains Without Hitting. - Yeshwanth Cherapanamjeri; Peter L. Bartlett (COLT, 2019)

Fast Mean Estimation with Sub-Gaussian Rates. - Yeshwanth Cherapanamjeri; Nicolas Flammarion; Peter L. Bartlett (COLT, 2019)

Testing Markov Chains without Hitting. - Yeshwanth Cherapanamjeri; Peter L. Bartlett (CoRR, 2019)

List Decodable Mean Estimation in Nearly Linear Time. - Yeshwanth Cherapanamjeri; Sidhanth Mohanty; Morris Yau (FOCS, 2020)

On Adaptive Distance Estimation. - Yeshwanth Cherapanamjeri; Jelani Nelson (NeurIPS, 2020)

Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond. - Yeshwanth Cherapanamjeri; Samuel B. Hopkins 001; Tarun Kathuria; Prasad Raghavendra; Nilesh Tripuraneni (STOC, 2020)

Optimal Robust Linear Regression in Nearly Linear Time. - Yeshwanth Cherapanamjeri; Efe Aras; Nilesh Tripuraneni; Michael I. Jordan; Nicolas Flammarion; Peter L. Bartlett (CoRR, 2020)

Adversarial Examples in Multi-Layer Random ReLU Networks. - Peter L. Bartlett; Sébastien Bubeck; Yeshwanth Cherapanamjeri (NeurIPS, 2021)

A single gradient step finds adversarial examples on random two-layers neural networks. - Sébastien Bubeck; Yeshwanth Cherapanamjeri; Gauthier Gidel; Remi Tachet des Combes (NeurIPS, 2021)

Optimal Mean Estimation without a Variance. - Yeshwanth Cherapanamjeri; Nilesh Tripuraneni; Peter L. Bartlett; Michael I. Jordan (COLT, 2022)

Estimation of Standard Auction Models. - Yeshwanth Cherapanamjeri; Constantinos Daskalakis; Andrew Ilyas; Manolis Zampetakis (EC, 2022)

Uniform approximations for Randomized Hadamard Transforms with applications. - Yeshwanth Cherapanamjeri; Jelani Nelson (STOC, 2022)

The One-Inclusion Graph Algorithm is not Always Optimal. - Ishaq Aden-Ali; Yeshwanth Cherapanamjeri; Abhishek Shetty; Nikita Zhivotovskiy (COLT, 2023)

Optimal PAC Bounds without Uniform Convergence. - Ishaq Aden-Ali; Yeshwanth Cherapanamjeri; Abhishek Shetty; Nikita Zhivotovskiy (FOCS, 2023)

Robust Algorithms on Adaptive Inputs from Bounded Adversaries. - Yeshwanth Cherapanamjeri; Sandeep Silwal; David P. Woodruff; Fred Zhang; Qiuyi Zhang 001; Samson Zhou (ICLR, 2023)

Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. - Yeshwanth Cherapanamjeri; Sandeep Silwal; David P. Woodruff; Samson Zhou (SODA, 2023)

What Makes a Good Fisherman? Linear Regression under Self-Selection Bias. - Yeshwanth Cherapanamjeri; Constantinos Daskalakis; Andrew Ilyas; Manolis Zampetakis (STOC, 2023)

An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification. - Aliyah R. Hsu; Yeshwanth Cherapanamjeri; Briton Park; Tristan Naumann; Anobel Y. Odisho; Bin Yu 001 (CoRR, 2023)

Statistical Barriers to Affine-equivariant Estimation. - Zihao Chen; Yeshwanth Cherapanamjeri (CoRR, 2023)

Recent Developments in Robust Statistics - Yeshwanth Cherapanamjeri (2023)

Computing Approximate Centerpoints in Polynomial Time. - Yeshwanth Cherapanamjeri (FOCS, 2024)

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making. - Aliyah R. Hsu; Yeshwanth Cherapanamjeri; Briton Park; Tristan Naumann; Anobel Y. Odisho; Bin Yu 001 (ICLR, 2024)

Mechanistic Interpretation through Contextual Decomposition in Transformers. - Aliyah R. Hsu; Yeshwanth Cherapanamjeri; Anobel Y. Odisho; Peter R. Carroll; Bin Yu 001 (CoRR, 2024)

Heavy-tailed Contamination is Easier than Adversarial Contamination. - Yeshwanth Cherapanamjeri; Daniel Lee (CoRR, 2024)

Terminal Embeddings in Sublinear Time. - Yeshwanth Cherapanamjeri; Jelani Nelson (TheoretiCS, 2024)

The Space Complexity of Learning-Unlearning Algorithms (extended abstract). - Yeshwanth Cherapanamjeri; Sumegba Garg; Nived Rajaraman; Ayush Sekhari; Abhishek Shetty (COLT, 2025)

Heavy-tailed Estimation is Easier than Adversarial Contamination. - Yeshwanth Cherapanamjeri; Daniel Lee (COLT, 2025)

How Much is a Noisy Image Worth? Data Scaling Laws for Ambient Diffusion. - Giannis Daras; Yeshwanth Cherapanamjeri; Constantinos Daskalakis (ICLR, 2025)

Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition. - Aliyah R. Hsu; Georgia Zhou; Yeshwanth Cherapanamjeri; Yaxuan Huang; Anobel Y. Odisho; Peter R. Carroll; Bin Yu 001 (ICLR, 2025)

The Space Complexity of Learning-Unlearning Algorithms. - Yeshwanth Cherapanamjeri; Sumegha Garg; Nived Rajaraman; Ayush Sekhari; Abhishek Shetty (CoRR, 2025)