Yeshwanth Cherapanamjeri

According to our database, Yeshwanth Cherapanamjeri authored at least 29 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Terminal Embeddings in Sublinear Time.

Yeshwanth Cherapanamjeri, Jelani Nelson

TheoretiCS, 2024

Heavy-tailed Contamination is Easier than Adversarial Contamination.

Yeshwanth Cherapanamjeri, Daniel Lee

CoRR, 2024

How much is a noisy image worth? Data Scaling Laws for Ambient Diffusion.

Giannis Daras, Yeshwanth Cherapanamjeri, Constantinos Daskalakis

CoRR, 2024

Mechanistic Interpretation through Contextual Decomposition in Transformers.

Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Anobel Y. Odisho, Peter R. Carroll, Bin Yu

CoRR, 2024

Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making.

Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Computing Approximate Centerpoints in Polynomial Time.

Yeshwanth Cherapanamjeri

Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

2023

Recent Developments in Robust Statistics

Yeshwanth Cherapanamjeri

PhD thesis, 2023

Statistical Barriers to Affine-equivariant Estimation.

Zihao Chen, Yeshwanth Cherapanamjeri

CoRR, 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

CoRR, 2023

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

Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time.

Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou

Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Robust Algorithms on Adaptive Inputs from Bounded Adversaries.

Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Optimal PAC Bounds without Uniform Convergence.

Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

The One-Inclusion Graph Algorithm is not Always Optimal.

Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Uniform approximations for Randomized Hadamard Transforms with applications.

Yeshwanth Cherapanamjeri, Jelani Nelson

Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Estimation of Standard Auction Models.

Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis

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.

Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter L. Bartlett, Michael I. Jordan

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.

Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes

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.

Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri

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.

Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni, Michael I. Jordan, Nicolas Flammarion, Peter L. Bartlett

CoRR, 2020

Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond.

Yeshwanth Cherapanamjeri, Samuel B. Hopkins, Tarun Kathuria, Prasad Raghavendra, Nilesh Tripuraneni

Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

On Adaptive Distance Estimation.

Yeshwanth Cherapanamjeri, Jelani Nelson

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.

Yeshwanth Cherapanamjeri, Sidhanth Mohanty, Morris Yau

Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

2019

Testing Markov Chains without Hitting.

Yeshwanth Cherapanamjeri, Peter L. Bartlett

CoRR, 2019

Fast Mean Estimation with Sub-Gaussian Rates.

Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett

Proceedings of the Conference on Learning Theory, 2019

Testing Symmetric Markov Chains Without Hitting.

Yeshwanth Cherapanamjeri, Peter L. Bartlett

Proceedings of the Conference on Learning Theory, 2019

2017

Thresholding based Efficient Outlier Robust PCA.

Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli

CoRR, 2017

Nearly Optimal Robust Matrix Completion.

Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain

Proceedings of the 34th International Conference on Machine Learning, 2017

Thresholding Based Outlier Robust PCA.

Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli

Proceedings of the 30th Conference on Learning Theory, 2017