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ORCIDYeshwanth Cherapanamjeri
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2020 – today
- 2024
[j1]Yeshwanth Cherapanamjeri, Jelani Nelson:
Terminal Embeddings in Sublinear Time. TheoretiCS 3 (2024)- [c19]Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu:
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making. ICLR 2024 - [i22]Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Anobel Y. Odisho, Peter R. Carroll, Bin Yu:
Mechanistic Interpretation through Contextual Decomposition in Transformers. CoRR abs/2407.00886 (2024) - 2023
- [b1]Yeshwanth Cherapanamjeri:
Recent Developments in Robust Statistics. University of California, Berkeley, USA, 2023 - [c18]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
The One-Inclusion Graph Algorithm is not Always Optimal. COLT 2023: 72-88 - [c17]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
Optimal PAC Bounds without Uniform Convergence. FOCS 2023: 1203-1223 - [c16]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou:
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. ICLR 2023 - [c15]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA 2023: 4026-4049 - [c14]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis
:
What Makes a Good Fisherman? Linear Regression under Self-Selection Bias. STOC 2023: 1699-1712 - [i21]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi Zhang, Samson Zhou:
Robust Algorithms on Adaptive Inputs from Bounded Adversaries. CoRR abs/2304.07413 (2023) - [i20]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
Optimal PAC Bounds Without Uniform Convergence. CoRR abs/2304.09167 (2023) - [i19]Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu:
An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification. CoRR abs/2305.17588 (2023) - [i18]Zihao Chen, Yeshwanth Cherapanamjeri:
Statistical Barriers to Affine-equivariant Estimation. CoRR abs/2310.10758 (2023) - 2022
- [c13]Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter L. Bartlett, Michael I. Jordan:
Optimal Mean Estimation without a Variance. COLT 2022: 356-357 - [c12]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
Estimation of Standard Auction Models. EC 2022: 602-603 - [c11]Yeshwanth Cherapanamjeri, Jelani Nelson:
Uniform approximations for Randomized Hadamard Transforms with applications. STOC 2022: 659-671 - [i17]Yeshwanth Cherapanamjeri, Jelani Nelson:
Uniform Approximations for Randomized Hadamard Transforms with Applications. CoRR abs/2203.01599 (2022) - [i16]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
Estimation of Standard Auction Models. CoRR abs/2205.02060 (2022) - [i15]Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis:
What Makes A Good Fisherman? Linear Regression under Self-Selection Bias. CoRR abs/2205.03246 (2022) - [i14]Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Samson Zhou:
Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR abs/2211.09964 (2022) - [i13]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
The One-Inclusion Graph Algorithm is not Always Optimal. CoRR abs/2212.09270 (2022) - 2021
- [c10]Yeshwanth Cherapanamjeri, Jelani Nelson:
Terminal Embeddings in Sublinear Time. FOCS 2021: 1209-1216 - [c9]Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri:
Adversarial Examples in Multi-Layer Random ReLU Networks. NeurIPS 2021: 9241-9252 - [c8]Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes:
A single gradient step finds adversarial examples on random two-layers neural networks. NeurIPS 2021: 10081-10091 - [i12]Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Rémi Tachet des Combes:
A single gradient step finds adversarial examples on random two-layers neural networks. CoRR abs/2104.03863 (2021) - [i11]Peter L. Bartlett, Sébastien Bubeck, Yeshwanth Cherapanamjeri:
Adversarial Examples in Multi-Layer Random ReLU Networks. CoRR abs/2106.12611 (2021) - [i10]Yeshwanth Cherapanamjeri, Jelani Nelson:
Terminal Embeddings in Sublinear Time. CoRR abs/2110.08691 (2021) - 2020
- [c7]Yeshwanth Cherapanamjeri, Sidhanth Mohanty, Morris Yau:
List Decodable Mean Estimation in Nearly Linear Time. FOCS 2020: 141-148 - [c6]Yeshwanth Cherapanamjeri, Jelani Nelson:
On Adaptive Distance Estimation. NeurIPS 2020 - [c5]Yeshwanth Cherapanamjeri, Samuel B. Hopkins, Tarun Kathuria, Prasad Raghavendra, Nilesh Tripuraneni:
Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond. STOC 2020: 601-609 - [i9]Yeshwanth Cherapanamjeri, Sidhanth Mohanty, Morris Yau:
List Decodable Mean Estimation in Nearly Linear Time. CoRR abs/2005.09796 (2020) - [i8]Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni, Michael I. Jordan, Nicolas Flammarion, Peter L. Bartlett:
Optimal Robust Linear Regression in Nearly Linear Time. CoRR abs/2007.08137 (2020) - [i7]Yeshwanth Cherapanamjeri, Jelani Nelson:
On Adaptive Distance Estimation. CoRR abs/2010.11252 (2020) - [i6]Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter L. Bartlett, Michael I. Jordan:
Optimal Mean Estimation without a Variance. CoRR abs/2011.12433 (2020)
2010 – 2019
- 2019
- [c4]Yeshwanth Cherapanamjeri, Peter L. Bartlett:
Testing Symmetric Markov Chains Without Hitting. COLT 2019: 758-785 - [c3]Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett:
Fast Mean Estimation with Sub-Gaussian Rates. COLT 2019: 786-806 - [i5]Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett:
Fast Mean Estimation with Sub-Gaussian Rates. CoRR abs/1902.01998 (2019) - [i4]Yeshwanth Cherapanamjeri, Peter L. Bartlett:
Testing Markov Chains without Hitting. CoRR abs/1902.01999 (2019) - [i3]Yeshwanth Cherapanamjeri, Samuel B. Hopkins, Tarun Kathuria, Prasad Raghavendra, Nilesh Tripuraneni:
Algorithms for Heavy-Tailed Statistics: Regression, Covariance Estimation, and Beyond. CoRR abs/1912.11071 (2019) - 2017
- [c2]Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli:
Thresholding Based Outlier Robust PCA. COLT 2017: 593-628 - [c1]Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain:
Nearly Optimal Robust Matrix Completion. ICML 2017: 797-805 - [i2]Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli:
Thresholding based Efficient Outlier Robust PCA. CoRR abs/1702.05571 (2017) - 2016
- [i1]Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain:
Nearly-optimal Robust Matrix Completion. CoRR abs/1606.07315 (2016)
Coauthor Index
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last updated on 2024-09-10 23:43 CEST by the dblp team
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