| Learning theory and algorithms for revenue optimization in second price auctions with reserve AM Medina, M Mohri Proceedings of the 31st International Conference on Machine Learning (ICML …, 2014 | 89 | 2014 |
| Machine learning and optimization A Munoz URL: https://www. cims. nyu. edu/~ munoz/files/ml_optimization. pdf …, 2014 | 81 | 2014 |
| New Analysis and Algorithm for Learning with Drifting Distributions M Mohri, AM Medina Arxiv preprint arXiv:1205.4343, 2012 | 41 | 2012 |
| Optimal regret minimization in posted-price auctions with strategic buyers M Mohri, A Munoz Advances in Neural Information Processing Systems, 1871-1879, 2014 | 38 | 2014 |
| Revenue optimization against strategic buyers M Mohri, A Munoz Advances in Neural Information Processing Systems, 2530-2538, 2015 | 25 | 2015 |
| Revenue optimization with approximate bid predictions AM Medina, S Vassilvitskii Proceedings of the 31st International Conference on Neural Information …, 2017 | 24 | 2017 |
| Learning algorithms for second-price auctions with reserve M Mohri, AM Medina The Journal of Machine Learning Research 17 (1), 2632-2656, 2016 | 21 | 2016 |
| Adaptation algorithm and theory based on generalized discrepancy C Cortes, M Mohri, A Muñoz Medina Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 19 | 2015 |
| Adaptation based on generalized discrepancy C Cortes, M Mohri, AM Medina The Journal of Machine Learning Research 20 (1), 1-30, 2019 | 18 | 2019 |
| No-regret algorithms for heavy-tailed linear bandits AM Medina, S Yang International Conference on Machine Learning, 1642-1650, 2016 | 11 | 2016 |
| Testing incentive compatibility in display ad auctions S Lahaie, A Munoz Medina, B Sivan, S Vassilvitskii Proceedings of the 2018 World Wide Web Conference, 1419-1428, 2018 | 9 | 2018 |
| Non-parametric revenue optimization for generalized second price auctions M Mohri, AM Medina arXiv preprint arXiv:1506.02719, 2015 | 9 | 2015 |
| Private covariance estimation via iterative eigenvector sampling K Amin, T Dick, A Kulesza, AM Medina, S Vassilvitskii 2018 NIPS workshop in Privacy-Preserving Machine Learning 250, 2018 | 4 | 2018 |
| Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy K Amin, A Kulesza, A Munoz, S Vassilvtiskii International Conference on Machine Learning, 263-271, 2019 | 3 | 2019 |
| Learning battery consumption of mobile devices P Eastham, AM Medina, A Sharma, U Syed, S Vassilvitskii, F Yu Proc. 33rd Int. Conf. Mach. Learn.(JMLR: W&CP) 48, 2016 | 3 | 2016 |
| Revenue optimization in posted-price auctions with strategic buyers M Mohri, AM Medina arXiv preprint arXiv:1411.6305, 2014 | 3 | 2014 |
| Differentially Private Covariance Estimation K Amin, T Dick, A Kulesza, A Munoz, S Vassilvitskii Advances in Neural Information Processing Systems, 14190-14199, 2019 | 1 | 2019 |
| Online Learning for Non-Stationary A/B Tests A Muñoz Medina, S Vassilvitskii, D Yin Proceedings of the 27th ACM International Conference on Information and …, 2018 | 1 | 2018 |
| Learning mobile phone battery consumptions AM Medina, A Sharma, F Yu, P Eastham, S Vassilvitskii, U Syed | 1 | 2016 |
| Learning Theory and Algorithms for Auctioning and Adaptation Problems AM Medina New York University, 2015 | 1 | 2015 |
