Yeshwanth Cherapanamjeri

52 papers A* 24Journal 27

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition. ICLR Aliyah R. Hsu, Georgia Zhou, Yeshwanth Cherapanamjeri, Yaxuan Huang, Anobel Y. Odisho, Peter R. Carroll, Bin Yu
2025	A*	`conf`	Heavy-tailed Estimation is Easier than Adversarial Contamination. COLT Yeshwanth Cherapanamjeri, Daniel Lee
2025	A*	`conf`	How Much is a Noisy Image Worth? Data Scaling Laws for Ambient Diffusion. ICLR Giannis Daras, Yeshwanth Cherapanamjeri, Constantinos Daskalakis
2025	J	`jnl`	Learning Correlated Reward Models: Statistical Barriers and Opportunities. CoRR Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Gabriele Farina, Sobhan Mohammadpour
2025	A*	`conf`	The Space Complexity of Learning-Unlearning Algorithms (extended abstract). COLT Yeshwanth Cherapanamjeri, Sumegba Garg, Nived Rajaraman, Ayush Sekhari, Abhishek Shetty
2025	J	`jnl`	The Space Complexity of Learning-Unlearning Algorithms. CoRR Yeshwanth Cherapanamjeri, Sumegha Garg, Nived Rajaraman, Ayush Sekhari, Abhishek Shetty
2024	A*	`conf`	Computing Approximate Centerpoints in Polynomial Time. FOCS Yeshwanth Cherapanamjeri
2024	A*	`conf`	Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making. ICLR Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
2024	J	`jnl`	Heavy-tailed Contamination is Easier than Adversarial Contamination. CoRR Yeshwanth Cherapanamjeri, Daniel Lee
2024	J	`jnl`	How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion. CoRR Giannis Daras, Yeshwanth Cherapanamjeri, Constantinos Daskalakis
2024	J	`jnl`	Mechanistic Interpretation through Contextual Decomposition in Transformers. CoRR Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Anobel Y. Odisho, Peter R. Carroll, Bin Yu
2024	J	`jnl`	Terminal Embeddings in Sublinear Time. TheoretiCS Yeshwanth Cherapanamjeri, Jelani Nelson
2023	J	`jnl`	An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification. CoRR Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
2023	A*	`conf`	Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
2023	J	`jnl`	Optimal PAC Bounds Without Uniform Convergence. CoRR Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2023	A*	`conf`	Optimal PAC Bounds without Uniform Convergence. FOCS Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2023	—	`—`	Recent Developments in Robust Statistics Yeshwanth Cherapanamjeri
2023	A*	`conf`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	J	`jnl`	Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou
2023	J	`jnl`	Statistical Barriers to Affine-equivariant Estimation. CoRR Zihao Chen, Yeshwanth Cherapanamjeri
2023	A*	`conf`	The One-Inclusion Graph Algorithm is not Always Optimal. COLT Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2023	A*	`conf`	What Makes a Good Fisherman? Linear Regression under Self-Selection Bias. STOC Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
2022	A*	`conf`	Estimation of Standard Auction Models. EC Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
2022	J	`jnl`	Estimation of Standard Auction Models. CoRR Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
2022	J	`jnl`	Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou
2022	A*	`conf`	Optimal Mean Estimation without a Variance. COLT Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter L. Bartlett, Michael I. Jordan
2022	J	`jnl`	The One-Inclusion Graph Algorithm is not Always Optimal. CoRR Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy
2022	J	`jnl`	Uniform Approximations for Randomized Hadamard Transforms with Applications. CoRR Yeshwanth Cherapanamjeri, Jelani Nelson
2022	A*	`conf`	Uniform approximations for Randomized Hadamard Transforms with applications. STOC Yeshwanth Cherapanamjeri, Jelani Nelson
2022	J	`jnl`	What Makes A Good Fisherman? Linear Regression under Self-Selection Bias. CoRR Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
2021	A*	`conf`	A single gradient step finds adversarial examples on random two-layers neural networks. NeurIPS Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
2021	J	`jnl`	A single gradient step finds adversarial examples on random two-layers neural networks. CoRR Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Rémi Tachet des Combes
2021	A*	`conf`	Adversarial Examples in Multi-Layer Random ReLU Networks. NeurIPS Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri
2021	J	`jnl`	Adversarial Examples in Multi-Layer Random ReLU Networks. CoRR Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri
2021	A*	`conf`	Terminal Embeddings in Sublinear Time. FOCS Yeshwanth Cherapanamjeri, Jelani Nelson
2021	J	`jnl`	Terminal Embeddings in Sublinear Time. CoRR Yeshwanth Cherapanamjeri, Jelani Nelson
2020	A*	`conf`	Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond. STOC Yeshwanth Cherapanamjeri, Samuel B. Hopkins, Tarun Kathuria, Prasad Raghavendra, Nilesh Tripuraneni
2020	A*	`conf`	List Decodable Mean Estimation in Nearly Linear Time. FOCS Yeshwanth Cherapanamjeri, Sidhanth Mohanty, Morris Yau
2020	J	`jnl`	List Decodable Mean Estimation in Nearly Linear Time. CoRR Yeshwanth Cherapanamjeri, Sidhanth Mohanty, Morris Yau
2020	A*	`conf`	On Adaptive Distance Estimation. NeurIPS Yeshwanth Cherapanamjeri, Jelani Nelson
2020	J	`jnl`	On Adaptive Distance Estimation. CoRR Yeshwanth Cherapanamjeri, Jelani Nelson
2020	J	`jnl`	Optimal Mean Estimation without a Variance. CoRR Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter L. Bartlett, Michael I. Jordan
2020	J	`jnl`	Optimal Robust Linear Regression in Nearly Linear Time. CoRR Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni, Michael I. Jordan, Nicolas Flammarion, Peter L. Bartlett
2019	J	`jnl`	Algorithms for Heavy-Tailed Statistics: Regression, Covariance Estimation, and Beyond. CoRR Yeshwanth Cherapanamjeri, Samuel B. Hopkins, Tarun Kathuria, Prasad Raghavendra, Nilesh Tripuraneni
2019	A*	`conf`	Fast Mean Estimation with Sub-Gaussian Rates. COLT Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett
2019	J	`jnl`	Fast Mean Estimation with Sub-Gaussian Rates. CoRR Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett
2019	J	`jnl`	Testing Markov Chains without Hitting. CoRR Yeshwanth Cherapanamjeri, Peter L. Bartlett
2019	A*	`conf`	Testing Symmetric Markov Chains Without Hitting. COLT Yeshwanth Cherapanamjeri, Peter L. Bartlett
2017	A*	`conf`	Nearly Optimal Robust Matrix Completion. ICML Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain
2017	A*	`conf`	Thresholding Based Outlier Robust PCA. COLT Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli
2017	J	`jnl`	Thresholding based Efficient Outlier Robust PCA. CoRR Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli
2016	J	`jnl`	Nearly-optimal Robust Matrix Completion. CoRR Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain