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Matthew Joseph
Matthew Joseph
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Fairness in learning: Classic and contextual bandits
M Joseph, M Kearns, JH Morgenstern, A Roth
Advances in Neural Information Processing Systems, 325-333, 2016
5162016
A Convex Framework for Fair Regression
R Berk, H Heidari, S Jabbari, M Joseph, M Kearns, J Morgenstern, S Neel, ...
arXiv preprint arXiv:1706.02409, 2017
3662017
Fairness in Reinforcement Learning
S Jabbari, M Joseph, M Kearns, J Morgenstern, A Roth
International Conference on Machine Learning, 1617-1626, 2017
232*2017
Meritocratic Fairness for Infinite and Contextual Bandits
M Joseph, M Kearns, J Morgenstern, S Neel, A Roth
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 158-163, 2018
176*2018
Local differential privacy for evolving data
M Joseph, A Roth, J Ullman, B Waggoner
Advances in Neural Information Processing Systems 31, 2375-2384, 2018
1012018
The role of interactivity in local differential privacy
M Joseph, J Mao, S Neel, A Roth
2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS …, 2019
872019
Connecting robust shuffle privacy and pan-privacy
V Balcer, A Cheu, M Joseph, J Mao
Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA …, 2021
432021
Locally private gaussian estimation
M Joseph, J Kulkarni, J Mao, SZ Wu
Advances in Neural Information Processing Systems, 2984-2993, 2019
432019
Differentially private quantiles
J Gillenwater, M Joseph, A Kulesza
International Conference on Machine Learning, 3713-3722, 2021
352021
Pan-private uniformity testing
K Amin, M Joseph, J Mao
Conference on Learning Theory, 183-218, 2020
342020
Exponential separations in local differential privacy
M Joseph, J Mao, A Roth
Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020
342020
Shuffle Private Stochastic Convex Optimization
A Cheu, M Joseph, J Mao, B Peng
International Conference on Learning Representations, 2022
252022
Plume: Differential Privacy at Scale
K Amin, J Gillenwater, M Joseph, A Kulesza, S Vassilvitskii
arXiv preprint arXiv:2201.11603, 2022
152022
A Joint Exponential Mechanism For Differentially Private Top-
J Gillenwater, M Joseph, A Munoz, MR Diaz
International Conference on Machine Learning, 7570-7582, 2022
92022
Easy Differentially Private Linear Regression
K Amin, M Joseph, M Ribero, S Vassilvitskii
ICLR 2023, 2023
42023
Better Private Linear Regression Through Better Private Feature Selection
T Dick, J Gillenwater, M Joseph
Advances in Neural Information Processing Systems 36, 2024
12024
Differential Privacy Beyond the Central Model
M Joseph
University of Pennsylvania, 2020
12020
Some Efficient and Optimal K-Norm Mechanisms
M Joseph, A Yu
arXiv preprint arXiv:2309.15790, 2023
2023
The Power of Interaction in Local Differential Privacy
M Joseph
2020
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Artikelen 1–19