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ORCIDAbhishek Shetty
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Journal Articles
- 2024
[j1]Nika Haghtalab
, Tim Roughgarden, Abhishek Shetty:
Smoothed Analysis with Adaptive Adversaries. J. ACM 71(3): 19 (2024)
Conference and Workshop Papers
- 2024
- [c17]Adam Block, Alexander Rakhlin, Abhishek Shetty:
On the Performance of Empirical Risk Minimization with Smoothed Data. COLT 2024: 596-629 - [c16]Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty:
Smooth Nash Equilibria: Algorithms and Complexity. ITCS 2024: 37:1-37:22 - 2023
- [c15]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
The One-Inclusion Graph Algorithm is not Always Optimal. COLT 2023: 72-88 - [c14]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
Optimal PAC Bounds without Uniform Convergence. FOCS 2023: 1203-1223 - [c13]Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty:
Smoothed Analysis of Sequential Probability Assignment. NeurIPS 2023 - [c12]Don Kurian Dennis, Abhishek Shetty, Anish Prasad Sevekari, Kazuhito Koishida, Virginia Smith:
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference. NeurIPS 2023 - [c11]Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty:
Adversarial Resilience in Sequential Prediction via Abstention. NeurIPS 2023 - 2022
- [c10]Abhishek Shetty, Raaz Dwivedi, Lester Mackey:
Distribution Compression in Near-Linear Time. ICLR 2022 - [c9]Nika Haghtalab, Yanjun Han, Abhishek Shetty, Kunhe Yang:
Oracle-Efficient Online Learning for Smoothed Adversaries. NeurIPS 2022 - [c8]Samuel B. Hopkins, Prasad Raghavendra, Abhishek Shetty:
Matrix discrepancy from Quantum communication. STOC 2022: 637-648 - 2021
- [c7]Eshan Chattopadhyay, Jason Gaitonde, Chin Ho Lee, Shachar Lovett, Abhishek Shetty:
Fractional Pseudorandom Generators from Any Fourier Level. CCC 2021: 10:1-10:24 - [c6]Nika Haghtalab, Tim Roughgarden, Abhishek Shetty:
Smoothed Analysis with Adaptive Adversaries. FOCS 2021: 942-953 - 2020
- [c5]Abhishek Panigrahi, Abhishek Shetty, Navin Goyal:
Effect of Activation Functions on the Training of Overparametrized Neural Nets. ICLR 2020 - [c4]Nika Haghtalab, Tim Roughgarden, Abhishek Shetty:
Smoothed Analysis of Online and Differentially Private Learning. NeurIPS 2020 - 2019
- [c3]Sudeep Raja Putta, Abhishek Shetty:
Exponential Weights on the Hypercube in Polynomial Time. AISTATS 2019: 1911-1919 - [c2]Navin Goyal, Abhishek Shetty:
Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature. COLT 2019: 1519-1561 - [c1]Navin Goyal, Abhishek Shetty:
Non-Gaussian component analysis using entropy methods. STOC 2019: 840-851
Informal and Other Publications
- 2024
- [i20]Parikshit Gopalan, Princewill Okoroafor, Prasad Raghavendra, Abhishek Shetty, Mihir Singhal:
Omnipredictors for Regression and the Approximate Rank of Convex Functions. CoRR abs/2401.14645 (2024) - [i19]Adam Block, Mark Bun, Rathin Desai, Abhishek Shetty, Steven Wu:
Oracle-Efficient Differentially Private Learning with Public Data. CoRR abs/2402.09483 (2024) - [i18]Adam Block, Alexander Rakhlin, Abhishek Shetty:
On the Performance of Empirical Risk Minimization with Smoothed Data. CoRR abs/2402.14987 (2024) - [i17]Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan:
Tolerant Algorithms for Learning with Arbitrary Covariate Shift. CoRR abs/2406.02742 (2024) - 2023
- [i16]Don Kurian Dennis, Abhishek Shetty, Anish Sevekari, Kazuhito Koishida, Virginia Smith:
Progressive Knowledge Distillation: Building Ensembles for Efficient Inference. CoRR abs/2302.10093 (2023) - [i15]Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty:
Smoothed Analysis of Sequential Probability Assignment. CoRR abs/2303.04845 (2023) - [i14]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
Optimal PAC Bounds Without Uniform Convergence. CoRR abs/2304.09167 (2023) - [i13]Surbhi Goel, Steve Hanneke, Shay Moran, Abhishek Shetty:
Adversarial Resilience in Sequential Prediction via Abstention. CoRR abs/2306.13119 (2023) - [i12]Constantinos Daskalakis, Noah Golowich, Nika Haghtalab, Abhishek Shetty:
Smooth Nash Equilibria: Algorithms and Complexity. CoRR abs/2309.12226 (2023) - 2022
- [i11]Nika Haghtalab, Yanjun Han, Abhishek Shetty, Kunhe Yang:
Oracle-Efficient Online Learning for Beyond Worst-Case Adversaries. CoRR abs/2202.08549 (2022) - [i10]Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy:
The One-Inclusion Graph Algorithm is not Always Optimal. CoRR abs/2212.09270 (2022) - 2021
- [i9]Nika Haghtalab, Tim Roughgarden, Abhishek Shetty:
Smoothed Analysis with Adaptive Adversaries. CoRR abs/2102.08446 (2021) - [i8]Samuel B. Hopkins, Prasad Raghavendra, Abhishek Shetty:
Matrix Discrepancy from Quantum Communication. CoRR abs/2110.10099 (2021) - [i7]Abhishek Shetty, Raaz Dwivedi, Lester Mackey:
Distribution Compression in Near-linear Time. CoRR abs/2111.07941 (2021) - 2020
- [i6]Nika Haghtalab, Tim Roughgarden, Abhishek Shetty:
Smoothed Analysis of Online and Differentially Private Learning. CoRR abs/2006.10129 (2020) - [i5]Eshan Chattopadhyay, Jason Gaitonde, Chin Ho Lee, Shachar Lovett, Abhishek Shetty:
Fractional Pseudorandom Generators from Any Fourier Level. CoRR abs/2008.01316 (2020) - [i4]Eshan Chattopadhyay, Jason Gaitonde, Abhishek Shetty:
Fractional Pseudorandom Generators from the $k$th Fourier Level. Electron. Colloquium Comput. Complex. TR20 (2020) - 2019
- [i3]Navin Goyal, Abhishek Shetty:
Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature. CoRR abs/1907.10531 (2019) - [i2]Abhishek Panigrahi, Abhishek Shetty, Navin Goyal:
Effect of Activation Functions on the Training of Overparametrized Neural Nets. CoRR abs/1908.05660 (2019) - 2018
- [i1]Navin Goyal, Abhishek Shetty:
Non-Gaussian Component Analysis using Entropy Methods. CoRR abs/1807.04936 (2018)
Coauthor Index
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