andres muñoz medina
andres muñoz medina
Google Research
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Title
Cited by
Cited by
Year
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
892014
Machine learning and optimization
A Munoz
URL: https://www. cims. nyu. edu/~ munoz/files/ml_optimization. pdf …, 2014
812014
New Analysis and Algorithm for Learning with Drifting Distributions
M Mohri, AM Medina
Arxiv preprint arXiv:1205.4343, 2012
412012
Optimal regret minimization in posted-price auctions with strategic buyers
M Mohri, A Munoz
Advances in Neural Information Processing Systems, 1871-1879, 2014
382014
Revenue optimization against strategic buyers
M Mohri, A Munoz
Advances in Neural Information Processing Systems, 2530-2538, 2015
252015
Revenue optimization with approximate bid predictions
AM Medina, S Vassilvitskii
Proceedings of the 31st International Conference on Neural Information …, 2017
242017
Learning algorithms for second-price auctions with reserve
M Mohri, AM Medina
The Journal of Machine Learning Research 17 (1), 2632-2656, 2016
212016
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
192015
Adaptation based on generalized discrepancy
C Cortes, M Mohri, AM Medina
The Journal of Machine Learning Research 20 (1), 1-30, 2019
182019
No-regret algorithms for heavy-tailed linear bandits
AM Medina, S Yang
International Conference on Machine Learning, 1642-1650, 2016
112016
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
92018
Non-parametric revenue optimization for generalized second price auctions
M Mohri, AM Medina
arXiv preprint arXiv:1506.02719, 2015
92015
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
42018
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
32019
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
32016
Revenue optimization in posted-price auctions with strategic buyers
M Mohri, AM Medina
arXiv preprint arXiv:1411.6305, 2014
32014
Differentially Private Covariance Estimation
K Amin, T Dick, A Kulesza, A Munoz, S Vassilvitskii
Advances in Neural Information Processing Systems, 14190-14199, 2019
12019
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
12018
Learning mobile phone battery consumptions
AM Medina, A Sharma, F Yu, P Eastham, S Vassilvitskii, U Syed
12016
Learning Theory and Algorithms for Auctioning and Adaptation Problems
AM Medina
New York University, 2015
12015
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