| Training gans with optimism C Daskalakis, A Ilyas, V Syrgkanis, H Zeng arXiv preprint arXiv:1711.00141, 2017 | 672 | 2017 |
| Orthogonal statistical learning DJ Foster, V Syrgkanis The Annals of Statistics 51 (3), 879-908, 2023 | 366 | 2023 |
| Fast convergence of regularized learning in games V Syrgkanis, A Agarwal, H Luo, RE Schapire Advances in Neural Information Processing Systems 28, 2015 | 358 | 2015 |
| Composable and efficient mechanisms V Syrgkanis, E Tardos Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013 | 286 | 2013 |
| 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 | 204 | 2019 |
| Minimax estimation of conditional moment models N Dikkala, G Lewis, L Mackey, V Syrgkanis Advances in Neural Information Processing Systems 33, 12248-12262, 2020 | 198* | 2020 |
| Bayesian incentive-compatible bandit exploration Y Mansour, A Slivkins, V Syrgkanis Proceedings of the Sixteenth ACM Conference on Economics and Computation …, 2015 | 198* | 2015 |
| Orthogonal random forest for causal inference M Oprescu, V Syrgkanis, ZS Wu International Conference on Machine Learning, 4932-4941, 2019 | 192* | 2019 |
| Bayesian exploration: Incentivizing exploration in bayesian games Y Mansour, A Slivkins, V Syrgkanis, ZS Wu arXiv preprint arXiv:1602.07570, 2016 | 154* | 2016 |
| Robust optimization for non-convex objectives RS Chen, B Lucier, Y Singer, V Syrgkanis Advances in Neural Information Processing Systems 30, 2017 | 151 | 2017 |
| The price of anarchy in auctions T Roughgarden, V Syrgkanis, E Tardos Journal of Artificial Intelligence Research 59, 59-101, 2017 | 143 | 2017 |
| Econometrics for learning agents D Nekipelov, V Syrgkanis, E Tardos Proceedings of the sixteenth acm conference on economics and computation, 1-18, 2015 | 133 | 2015 |
| Efficient algorithms for adversarial contextual learning V Syrgkanis, A Krishnamurthy, R Schapire International Conference on Machine Learning, 2159-2168, 2016 | 113 | 2016 |
| Sequential auctions and externalities RP Leme, V Syrgkanis, É Tardos Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete …, 2012 | 110 | 2012 |
| Machine learning estimation of heterogeneous treatment effects with instruments V Syrgkanis, V Lei, M Oprescu, M Hei, K Battocchi, G Lewis Advances in Neural Information Processing Systems 32, 2019 | 107 | 2019 |
| Genome-scale screens identify factors regulating tumor cell responses to natural killer cells M Sheffer, E Lowry, N Beelen, M Borah, SNA Amara, CC Mader, JA Roth, ... Nature Genetics 53 (8), 1196-1206, 2021 | 106 | 2021 |
| Accurate inference for adaptive linear models Y Deshpande, L Mackey, V Syrgkanis, M Taddy International Conference on Machine Learning, 1194-1203, 2018 | 105 | 2018 |
| Long story short: Omitted variable bias in causal machine learning V Chernozhukov, C Cinelli, W Newey, A Sharma, V Syrgkanis National Bureau of Economic Research, 2022 | 104* | 2022 |
| 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 | 104 | 2020 |
| 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 | 103 | 2016 |
Eva TardosProfessor of Computer Science, Cornell UniversityVerified email at cornell.edu
