| Informed truthfulness in multi-task peer prediction V Shnayder, A Agarwal, R Frongillo, DC Parkes Proceedings of the 2016 ACM Conference on Economics and Computation, 179-196, 2016 | 160 | 2016 |
| Learning with limited rounds of adaptivity: Coin tossing, multi-armed bandits, and ranking from pairwise comparisons A Agarwal, S Agarwal, S Assadi, S Khanna Conference on Learning Theory, 39-75, 2017 | 117 | 2017 |
| Accelerated spectral ranking A Agarwal, P Patil, S Agarwal International Conference on Machine Learning, 70-79, 2018 | 65 | 2018 |
| Peer prediction with heterogeneous users A Agarwal, D Mandal, DC Parkes, N Shah ACM Transactions on Economics and Computation (TEAC) 8 (1), 1-34, 2020 | 62 | 2020 |
| On consistent surrogate risk minimization and property elicitation A Agarwal, S Agarwal Conference on Learning Theory, 4-22, 2015 | 40 | 2015 |
| Stochastic submodular cover with limited adaptivity A Agarwal, S Assadi, S Khanna Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 26 | 2019 |
| Choice bandits A Agarwal, N Johnson, S Agarwal Advances in neural information processing systems 33, 18399-18410, 2020 | 23 | 2020 |
| A sharp memory-regret trade-off for multi-pass streaming bandits A Agarwal, S Khanna, P Patil Conference on Learning Theory, 1423-1462, 2022 | 15 | 2022 |
| Sublinear algorithms for hierarchical clustering A Agarwal, S Khanna, H Li, P Patil Advances in Neural Information Processing Systems 35, 3417-3430, 2022 | 14 | 2022 |
| Batched dueling bandits A Agarwal, R Ghuge, V Nagarajan International Conference on Machine Learning, 89-110, 2022 | 13 | 2022 |
| Stochastic dueling bandits with adversarial corruption A Agarwal, S Agarwal, P Patil Algorithmic Learning Theory, 217-248, 2021 | 13 | 2021 |
| Rank aggregation from pairwise comparisons in the presence of adversarial corruptions A Agarwal, S Agarwal, S Khanna, P Patil International Conference on Machine Learning, 85-95, 2020 | 13 | 2020 |
| Diversified recommendations for agents with adaptive preferences W Brown, A Agarwal Advances in Neural Information Processing Systems 35, 26066-26077, 2022 | 12 | 2022 |
| Gev-canonical regression for accurate binary class probability estimation when one class is rare A Agarwal, H Narasimhan, S Kalyanakrishnan, S Agarwal International Conference on Machine Learning, 1989-1997, 2014 | 11 | 2014 |
| Online recommendations for agents with discounted adaptive preferences A Agarwal, W Brown arXiv preprint arXiv:2302.06014, 2023 | 7 | 2023 |
| Parallel approximate maximum flows in near-linear work and polylogarithmic depth A Agarwal, S Khanna, H Li, P Patil, C Wang, N White, P Zhong Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2024 | 5 | 2024 |
| When can we track significant preference shifts in dueling bandits? J Suk, A Agarwal Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| PAC Top- Identification under SST in Limited Rounds A Agarwal, S Khanna, P Patil International Conference on Artificial Intelligence and Statistics, 6814-6839, 2022 | 3 | 2022 |
| An asymptotically optimal batched algorithm for the dueling bandit problem A Agarwal, R Ghuge Advances in Neural Information Processing Systems 35, 28914-28927, 2022 | 2 | 2022 |
| Semi-bandit learning for monotone stochastic optimization A Agarwal, R Ghuge, V Nagarajan 2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS …, 2024 | 1 | 2024 |
Shivani AgarwalUniversity of PennsylvaniaVerified email at seas.upenn.edu
