| Training gans with optimism C Daskalakis, A Ilyas, V Syrgkanis, H Zeng arXiv preprint arXiv:1711.00141, 2017 | 546 | 2017 |
| Fast convergence of regularized learning in games V Syrgkanis, A Agarwal, H Luo, RE Schapire Advances in Neural Information Processing Systems 28, 2015 | 264 | 2015 |
| Composable and efficient mechanisms V Syrgkanis, E Tardos Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013 | 257 | 2013 |
| Orthogonal statistical learning DJ Foster, V Syrgkanis The Annals of Statistics 51 (3), 879-908, 2023 | 224 | 2023 |
| Bayesian incentive-compatible bandit exploration Y Mansour, A Slivkins, V Syrgkanis Proceedings of the Sixteenth ACM Conference on Economics and Computation …, 2015 | 157* | 2015 |
| Orthogonal random forest for causal inference M Oprescu, V Syrgkanis, ZS Wu International Conference on Machine Learning, 4932-4941, 2019 | 129* | 2019 |
| Robust optimization for non-convex objectives RS Chen, B Lucier, Y Singer, V Syrgkanis Advances in Neural Information Processing Systems 30, 2017 | 127 | 2017 |
| Minimax estimation of conditional moment models N Dikkala, G Lewis, L Mackey, V Syrgkanis Advances in Neural Information Processing Systems 33, 12248-12262, 2020 | 123* | 2020 |
| The price of anarchy in auctions T Roughgarden, V Syrgkanis, E Tardos Journal of Artificial Intelligence Research 59, 59-101, 2017 | 116 | 2017 |
| Bayesian exploration: Incentivizing exploration in bayesian games Y Mansour, A Slivkins, V Syrgkanis, ZS Wu arXiv preprint arXiv:1602.07570, 2016 | 113* | 2016 |
| EconML: a Python package for ML-based heterogeneous treatment effects estimation K Battocchi, E Dillon, M Hei, G Lewis, P Oka, M Oprescu, V Syrgkanis Version 0. x, 2019 | 110 | 2019 |
| Sequential auctions and externalities RP Leme, V Syrgkanis, É Tardos Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete …, 2012 | 110 | 2012 |
| Econometrics for learning agents D Nekipelov, V Syrgkanis, E Tardos Proceedings of the sixteenth acm conference on economics and computation, 1-18, 2015 | 100 | 2015 |
| Learning and efficiency in games with dynamic population T Lykouris, V Syrgkanis, É Tardos Proceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete …, 2016 | 92 | 2016 |
| Efficient algorithms for adversarial contextual learning V Syrgkanis, A Krishnamurthy, R Schapire International Conference on Machine Learning, 2159-2168, 2016 | 91 | 2016 |
| Oracle-efficient online learning and auction design M Dudík, N Haghtalab, H Luo, RE Schapire, V Syrgkanis, JW Vaughan Journal of the ACM (JACM) 67 (5), 1-57, 2020 | 82 | 2020 |
| No-regret learning in Bayesian games J Hartline, V Syrgkanis, E Tardos Advances in Neural Information Processing Systems 28, 2015 | 79 | 2015 |
| Learning in auctions: Regret is hard, envy is easy C Daskalakis, V Syrgkanis 2016 ieee 57th annual symposium on foundations of computer science (focs …, 2016 | 77* | 2016 |
| Accurate inference for adaptive linear models Y Deshpande, L Mackey, V Syrgkanis, M Taddy International Conference on Machine Learning, 1194-1203, 2018 | 74 | 2018 |
| The curse of simultaneity RP Leme, V Syrgkanis, É Tardos Proceedings of the 3rd innovations in theoretical computer science …, 2012 | 71 | 2012 |
Eva TardosProfessor of Computer Science, Cornell University在 cornell.edu 的电子邮件经过验证
