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ORCIDAndrés Muñoz Medina
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2020 – today
- 2024
[c23]William Kong, Andrés Muñoz Medina, Mónica Ribero, Umar Syed:
DP-Auditorium: A Large-Scale Library for Auditing Differential Privacy. SP 2024: 110-126- [c22]Alessandro Epasto
, Hossein Esfandiari, Vahab Mirrokni, Andrés Muñoz Medina:
Smooth Anonymity for Sparse Graphs. WWW (Companion Volume) 2024: 621-624 - [e1]Luz Angelica Caudillo-Mata, Silvio Lattanzi, Andrés Muñoz Medina, Leman Akoglu, Aristides Gionis, Sergei Vassilvitskii:
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024. ACM 2024 [contents] - [i20]Róbert Istvan Busa-Fekete, Travis Dick, Claudio Gentile, Andrés Muñoz Medina, Adam D. Smith, Marika Swanberg:
Auditing Privacy Mechanisms via Label Inference Attacks. CoRR abs/2406.02797 (2024) - 2023
- [j3]CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andres Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong:
Measuring Re-identification Risk. Proc. ACM Manag. Data 1(2): 149:1-149:26 (2023) - [c21]Róbert Istvan Busa-Fekete, Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii:
Label differential privacy and private training data release. ICML 2023: 3233-3251 - [c20]Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong:
Differentially Private Continual Releases of Streaming Frequency Moment Estimations. ITCS 2023: 48:1-48:24 - [c19]Róbert Busa-Fekete, Heejin Choi, Travis Dick, Claudio Gentile, Andrés Muñoz Medina:
Easy Learning from Label Proportions. NeurIPS 2023 - [c18]Weiwei Kong, Andrés Muñoz Medina:
A Unified Fast Gradient Clipping Framework for DP-SGD. NeurIPS 2023 - [i19]Alessandro Epasto, Jieming Mao, Andres Muñoz Medina, Vahab Mirrokni, Sergei Vassilvitskii, Peilin Zhong:
Differentially Private Continual Releases of Streaming Frequency Moment Estimations. CoRR abs/2301.05605 (2023) - [i18]Róbert Istvan Busa-Fekete, Heejin Choi, Travis Dick, Claudio Gentile, Andrés Muñoz Medina:
Easy Learning from Label Proportions. CoRR abs/2302.03115 (2023) - [i17]CJ Carey, Travis Dick, Alessandro Epasto, Adel Javanmard, Josh Karlin, Shankar Kumar, Andrés Muñoz Medina, Vahab Mirrokni, Gabriel Henrique Nunes, Sergei Vassilvitskii, Peilin Zhong:
Measuring Re-identification Risk. CoRR abs/2304.07210 (2023) - [i16]Gecia Bravo Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andres Muñoz Medina, Umar Syed:
Private and Communication-Efficient Algorithms for Entropy Estimation. CoRR abs/2305.07751 (2023) - [i15]William Kong, Andrés Muñoz Medina, Mónica Ribero:
RényiTester: A Variational Approach to Testing Differential Privacy. CoRR abs/2307.05608 (2023) - [i14]William Kong, Andrés Muñoz Medina, Mónica Ribero:
DP-SGD for non-decomposable objective functions. CoRR abs/2310.03104 (2023) - 2022
- [c17]Jennifer Gillenwater, Matthew Joseph, Andres Muñoz Medina, Mónica Ribero Diaz:
A Joint Exponential Mechanism For Differentially Private Top-k. ICML 2022: 7570-7582 - [c16]Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii:
Scalable Differentially Private Clustering via Hierarchically Separated Trees. KDD 2022: 221-230 - [c15]Gecia Bravo Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andrés Muñoz Medina, Umar Syed:
Private and Communication-Efficient Algorithms for Entropy Estimation. NeurIPS 2022 - [i13]Gecia Bravo Hermsdorff, Róbert Busa-Fekete, Lee M. Gunderson, Andrés Muñoz Medina, Umar Syed:
Statistical anonymity: Quantifying reidentification risks without reidentifying users. CoRR abs/2201.12306 (2022) - [i12]Jennifer Gillenwater, Matthew Joseph, Andrés Muñoz Medina, Mónica Ribero:
A Joint Exponential Mechanism For Differentially Private Top-k. CoRR abs/2201.12333 (2022) - [i11]Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab S. Mirrokni, Andres Muñoz Medina, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii:
Scalable Differentially Private Clustering via Hierarchically Separated Trees. CoRR abs/2206.08646 (2022) - [i10]Hossein Esfandiari, Alessandro Epasto, Vahab S. Mirrokni, Andres Muñoz Medina, Sergei Vassilvitskii:
Smooth Anonymity for Sparse Binary Matrices. CoRR abs/2207.06358 (2022) - 2021
- [c14]Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik:
Private optimization without constraint violations. AISTATS 2021: 2557-2565 - [c13]Alessandro Epasto, Andrés Muñoz Medina, Steven Avery, Yijian Bai, Róbert Busa-Fekete, CJ Carey, Ya Gao, David Guthrie, Subham Ghosh, James Ioannidis, Junyi Jiao, Jakub Lacki, Jason Lee, Arne Mauser, Brian Milch, Vahab S. Mirrokni, Deepak Ravichandran, Wei Shi, Max Spero, Yunting Sun, Umar Syed, Sergei Vassilvitskii, Shuo Wang:
Clustering for Private Interest-based Advertising. KDD 2021: 2802-2810 - 2020
- [i9]Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik:
Private Optimization Without Constraint Violations. CoRR abs/2007.01181 (2020) - [i8]Andrés Muñoz Medina, Jenny Gillenwater:
Duff: A Dataset-Distance-Based Utility Function Family for the Exponential Mechanism. CoRR abs/2010.04235 (2020)
2010 – 2019
- 2019
- [j2]Corinna Cortes, Mehryar Mohri, Andrés Muñoz Medina:
Adaptation Based on Generalized Discrepancy. J. Mach. Learn. Res. 20: 1:1-1:30 (2019) - [c12]Kareem Amin, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii:
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy. ICML 2019: 263-271 - [c11]Kareem Amin, Travis Dick, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii:
Differentially Private Covariance Estimation. NeurIPS 2019: 14190-14199 - 2018
- [c10]Andrés Muñoz Medina, Sergei Vassilvitskii, Dong Yin:
Online Learning for Non-Stationary A/B Tests. CIKM 2018: 317-326 - [c9]Sébastien Lahaie, Andrés Muñoz Medina, Balasubramanian Sivan, Sergei Vassilvitskii:
Testing Incentive Compatibility in Display Ad Auctions. WWW 2018: 1419-1428 - [i7]Andrés Muñoz Medina, Sergei Vassilvitskii, Dong Yin:
Online Learning for Non-Stationary A/B Tests. CoRR abs/1802.05315 (2018) - 2017
- [c8]Andres Muñoz Medina, Sergei Vassilvitskii:
Revenue Optimization with Approximate Bid Predictions. NIPS 2017: 1858-1866 - [i6]Andrés Muñoz Medina, Sergei Vassilvitskii:
Revenue Optimization with Approximate Bid Predictions. CoRR abs/1706.04732 (2017) - 2016
- [j1]Mehryar Mohri, Andres Muñoz Medina:
Learning Algorithms for Second-Price Auctions with Reserve. J. Mach. Learn. Res. 17: 74:1-74:25 (2016) - [c7]Andres Muñoz Medina, Scott Yang:
No-Regret Algorithms for Heavy-Tailed Linear Bandits. ICML 2016: 1642-1650 - 2015
- [c6]Corinna Cortes, Mehryar Mohri, Andres Muñoz Medina:
Adaptation Algorithm and Theory Based on Generalized Discrepancy. KDD 2015: 169-178 - [c5]Mehryar Mohri, Andres Muñoz Medina:
Revenue Optimization against Strategic Buyers. NIPS 2015: 2530-2538 - [c4]Mehryar Mohri, Andres Muñoz Medina:
Non-parametric Revenue Optimization for Generalized Second Price auctions.. UAI 2015: 612-621 - [i5]Mehryar Mohri, Andres Muñoz Medina:
Non-parametric Revenue Optimization for Generalized Second Price Auctions. CoRR abs/1506.02719 (2015) - 2014
- [c3]Mehryar Mohri, Andres Muñoz Medina:
Learning Theory and Algorithms for revenue optimization in second price auctions with reserve. ICML 2014: 262-270 - [c2]Mehryar Mohri, Andres Muñoz Medina:
Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers. NIPS 2014: 1871-1879 - [i4]Corinna Cortes, Mehryar Mohri, Andres Muñoz Medina:
Adaptation Algorithm and Theory Based on Generalized Discrepancy. CoRR abs/1405.1503 (2014) - [i3]Mehryar Mohri, Andres Muñoz Medina:
Revenue Optimization in Posted-Price Auctions with Strategic Buyers. CoRR abs/1411.6305 (2014) - 2013
- [i2]Mehryar Mohri, Andres Muñoz Medina:
Learning Theory and Algorithms for Revenue Optimization in Second-Price Auctions with Reserve. CoRR abs/1310.5665 (2013) - 2012
- [c1]Mehryar Mohri, Andres Muñoz Medina:
New Analysis and Algorithm for Learning with Drifting Distributions. ALT 2012: 124-138 - [i1]Mehryar Mohri, Andres Muñoz Medina:
New Analysis and Algorithm for Learning with Drifting Distributions. CoRR abs/1205.4343 (2012)
Coauthor Index
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last updated on 2024-09-23 00:30 CEST by the dblp team
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