An Optimal Private Stochastic-MAB Algorithm Based on an Optimal Private Stopping Rule

22 May 2019

Papers citing "An Optimal Private Stochastic-MAB Algorithm Based on an Optimal Private Stopping Rule"

13 / 13 papers shown

Title
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret Bingshan Hu Zhiming Huang Tianyue H. Zhang Mathias Lécuyer Nidhi Hegde 19 0 0 05 May 2025
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence Achraf Azize Marc Jourdan Aymen Al Marjani D. Basu 44 3 0 05 Sep 2023
Concentrated Differential Privacy for Bandits Achraf Azize D. Basu 41 4 0 01 Sep 2023
Unbounded Differentially Private Quantile and Maximum Estimation D. Durfee 59 6 0 02 May 2023
On Private and Robust Bandits Yulian Wu Xingyu Zhou Youming Tao Di Wang 24 5 0 06 Feb 2023
(Private) Kernelized Bandits with Distributed Biased Feedback Fengjiao Li Xingyu Zhou Bo Ji 38 5 0 28 Jan 2023
Differentially Private Stochastic Linear Bandits: (Almost) for Free Osama A. Hanna Antonious M. Girgis Christina Fragouli Suhas Diggavi FedML 29 18 0 07 Jul 2022
Distributed Differential Privacy in Multi-Armed Bandits Sayak Ray Chowdhury Xingyu Zhou 40 12 0 12 Jun 2022
Differentially Private Regret Minimization in Episodic Markov Decision Processes Sayak Ray Chowdhury Xingyu Zhou 29 21 0 20 Dec 2021
Differentially Private Exploration in Reinforcement Learning with Linear Representation Paul Luyo Evrard Garcelon A. Lazaric Matteo Pirotta 60 11 0 02 Dec 2021
The Sparse Vector Technique, Revisited Haim Kaplan Yishay Mansour Uri Stemmer 43 17 0 02 Oct 2020
Privacy-preserving Q-Learning with Functional Noise in Continuous State Spaces Baoxiang Wang N. Hegde 17 64 0 30 Jan 2019
Bounded regret in stochastic multi-armed bandits Sébastien Bubeck Vianney Perchet Philippe Rigollet 71 91 0 06 Feb 2013