| Smoothed analysis with adaptive adversaries N Haghtalab, T Roughgarden, A Shetty 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 66 | 2022 |
| Smoothed Analysis of Online and Differentially Private Learning N Haghtalab, T Roughgarden, A Shetty Advances in Neural Information Processing Systems 33, 2020 | 64 | 2020 |
| Oracle-Efficient Online Learning for Smoothed Adversaries N Haghtalab, Y Han, A Shetty, K Yang Advances in Neural Information Processing Systems, 0 | 39* | |
| Effect of Activation Functions on the Training of Overparametrized Neural Nets A Panigrahi, A Shetty, N Goyal arXiv preprint arXiv:1908.05660, 2019 | 34 | 2019 |
| Matrix discrepancy from Quantum communication SB Hopkins, P Raghavendra, A Shetty Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 22 | 2022 |
| Distribution Compression in Near-Linear Time A Shetty, R Dwivedi, L Mackey arXiv preprint arXiv:2111.07941, 2021 | 22 | 2021 |
| Optimal pac bounds without uniform convergence I Aden-Ali, Y Cherapanamjeri, A Shetty, N Zhivotovskiy 2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS …, 2023 | 20 | 2023 |
| Fractional pseudorandom generators from any fourier level E Chattopadhyay, J Gaitonde, CH Lee, S Lovett, A Shetty arXiv preprint arXiv:2008.01316, 2020 | 15 | 2020 |
| Non-Gaussian component analysis using entropy methods N Goyal, A Shetty Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 14 | 2019 |
| Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature N Goyal, A Shetty Conference on Learning Theory, 1519-1561, 2019 | 13 | 2019 |
| Smoothed analysis of sequential probability assignment A Bhatt, N Haghtalab, A Shetty Advances in Neural Information Processing Systems 36, 79808-79831, 2023 | 11 | 2023 |
| Omnipredictors for regression and the approximate rank of convex functions P Gopalan, P Okoroafor, P Raghavendra, A Sherry, M Singhal The Thirty Seventh Annual Conference on Learning Theory, 2027-2070, 2024 | 8 | 2024 |
| The One-Inclusion Graph Algorithm is not Always Optimal I Aden-Ali, Y Cherapanamjeri, A Shetty, N Zhivotovskiy The Thirty Sixth Annual Conference on Learning Theory, 72-88, 2023 | 8 | 2023 |
| Adversarial resilience in sequential prediction via abstention S Goel, S Hanneke, S Moran, A Shetty Advances in Neural Information Processing Systems 36, 8027-8047, 2023 | 7 | 2023 |
| On the performance of empirical risk minimization with smoothed data A Block, A Rakhlin, A Shetty The Thirty Seventh Annual Conference on Learning Theory, 596-629, 2024 | 6 | 2024 |
| Smooth Nash Equilibria: Algorithms and Complexity C Daskalakis, N Golowich, N Haghtalab, A Shetty arXiv preprint arXiv:2309.12226, 2023 | 6 | 2023 |
| Oracle-efficient differentially private learning with public data A Block, M Bun, R Desai, A Shetty, SZ Wu Advances in Neural Information Processing Systems 37, 113191-113233, 2024 | 5 | 2024 |
| Progressive ensemble distillation: Building ensembles for efficient inference D Dennis, A Shetty, AP Sevekari, K Koishida, V Smith Advances in Neural Information Processing Systems 36, 43525-43543, 2023 | 4 | 2023 |
| Tolerant algorithms for learning with arbitrary covariate shift S Goel, A Shetty, K Stavropoulos, A Vasilyan Advances in Neural Information Processing Systems 37, 124979-125018, 2024 | 3 | 2024 |
| Low-Rank Thinning AM Carrell, A Gong, A Shetty, R Dwivedi, L Mackey arXiv preprint arXiv:2502.12063, 2025 | | 2025 |
Nika HaghtalabUniversity of California, BerkeleyVerified email at berkeley.edu
