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Private Matchings and Allocations

12 November 2013

Papers citing "Private Matchings and Allocations"

38 / 38 papers shown

Title
Towards Optimal Differentially Private Regret Bounds in Linear MDPs Sharan Sahu 124 0 0 12 Apr 2025
No-regret Exploration in Shuffle Private Reinforcement Learning Shaojie Bai Mohammad Sadegh Talebi Chengcheng Zhao Peng Cheng Jiming Chen OffRL 115 0 0 18 Nov 2024
Enabling Humanitarian Applications with Targeted Differential Privacy Nitin Kohli J. Blumenstock 68 0 0 24 Aug 2024
Asymptotically Fair and Truthful Allocation of Public Goods Pouya Kananian Arnesh Sujanani Seyed Majid Zahedi 45 0 0 24 Apr 2024
Differentially Private Reinforcement Learning with Self-Play Dan Qiao Yu Wang 92 0 0 11 Apr 2024
Fine-Grained Privacy Guarantees for Coverage Problems Laxman Dhulipala George Z. Li 43 1 0 05 Mar 2024
Differentially Private High Dimensional Bandits Apurv Shukla 61 0 0 06 Feb 2024
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning Zebang Shen Jiayuan Ye Anmin Kang Hamed Hassani Reza Shokri FedML 102 18 0 11 Sep 2023
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards Yulian Wu Xingyu Zhou Sayak Ray Chowdhury Di Wang 92 2 0 01 Jun 2023
Learning across Data Owners with Joint Differential Privacy Yangsibo Huang Haotian Jiang Daogao Liu Mohammad Mahdian Jieming Mao Vahab Mirrokni FedML 82 0 0 25 May 2023
Differentially Private Online Item Pricing Joon Suk Huh 34 0 0 19 May 2023
Near-Optimal Differentially Private Reinforcement Learning Dan Qiao Yu Wang 95 14 0 09 Dec 2022
Truthful Generalized Linear Models Yuan Qiu Jinyan Liu Di Wang FedML 82 3 0 16 Sep 2022
Shuffle Private Linear Contextual Bandits Sayak Ray Chowdhury Xingyu Zhou FedML 98 27 0 11 Feb 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning A. Bietti Chen-Yu Wei Miroslav Dudík John Langford Zhiwei Steven Wu FedML 102 50 0 10 Feb 2022
Improved Regret for Differentially Private Exploration in Linear MDP Dung Daniel Ngo G. Vietri Zhiwei Steven Wu 96 8 0 02 Feb 2022
Differentially Private Reinforcement Learning with Linear Function Approximation Xingyu Zhou 97 26 0 18 Jan 2022
Differentially Private Regret Minimization in Episodic Markov Decision Processes Sayak Ray Chowdhury Xingyu Zhou 85 22 0 20 Dec 2021
Differentially Private Exploration in Reinforcement Learning with Linear Representation Paul Luyo Evrard Garcelon A. Lazaric Matteo Pirotta 139 11 0 02 Dec 2021
Privately Publishable Per-instance Privacy Rachel Redberg Yu Wang 103 18 0 03 Nov 2021
Private Multi-Task Learning: Formulation and Applications to Federated Learning Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 111 20 0 30 Aug 2021
Adaptive Control of Differentially Private Linear Quadratic Systems Sayak Ray Chowdhury Xingyu Zhou Ness B. Shroff 75 10 0 26 Aug 2021
Federated $f$ -Differential Privacy Qinqing Zheng Shuxiao Chen Qi Long Weijie J. Su FedML 149 55 0 22 Feb 2021
A Distributed Differentially Private Algorithm for Resource Allocation in Unboundedly Large Settings Panayiotis Danassis Aleksei Triastcyn Boi Faltings 97 5 0 16 Nov 2020
Private Reinforcement Learning with PAC and Regret Guarantees G. Vietri Borja Balle A. Krishnamurthy Zhiwei Steven Wu 64 63 0 18 Sep 2020
Private Optimization Without Constraint Violations Andrés Munoz Medina Umar Syed Sergei Vassilvitskii Ellen Vitercik 34 10 0 02 Jul 2020
Optimal, Truthful, and Private Securities Lending Emily Diana Michael Kearns Seth Neel Aaron Roth 20 3 0 12 Dec 2019
Facility Location Problem in Differential Privacy Model Revisited Yunus Esencayi Marco Gaboardi Shi Li Di Wang 47 12 0 26 Oct 2019
Private Incremental Regression S. Kasiviswanathan Kobbi Nissim Hongxia Jin 39 14 0 04 Jan 2017
The Possibilities and Limitations of Private Prediction Markets Rachel Cummings David M. Pennock Jennifer Wortman Vaughan 16 20 0 24 Feb 2016
Technical Privacy Metrics: a Systematic Survey Isabel Wagner D. Eckhoff 104 172 0 01 Dec 2015
Shortest Paths and Distances with Differential Privacy Adam Sealfon 58 58 0 14 Nov 2015
Designing Incentive Schemes For Privacy-Sensitive Users Chong Huang Lalitha Sankar Anand D. Sarwate 34 4 0 07 Aug 2015
Truthful Linear Regression Rachel Cummings Stratis Ioannidis Katrina Ligett FedML 77 61 0 10 Jun 2015
Gradual Release of Sensitive Data under Differential Privacy Fragkiskos Koufogiannis Shuo Han George J. Pappas 110 36 0 02 Apr 2015
Buying Private Data without Verification Arpita Ghosh Katrina Ligett Aaron Roth Grant Schoenebeck FedML 96 74 0 24 Apr 2014
Asymptotically Truthful Equilibrium Selection in Large Congestion Games Ryan M. Rogers Aaron Roth 131 51 0 11 Nov 2013
Mechanism Design in Large Games: Incentives and Privacy Michael Kearns Mallesh M. Pai Aaron Roth Jonathan R. Ullman 193 184 0 17 Jul 2012