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"

9 / 9 papers shown

Title
Differentially Private Contextual Linear Bandits R. Shariff Or Sheffet 43 119 0 28 Sep 2018
High-confidence error estimates for learned value functions Touqir Sajed Wesley Chung Martha White OffRL 34 9 0 28 Aug 2018
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem Sampath Kannan Jamie Morgenstern Aaron Roth Bo Waggoner Zhiwei Steven Wu 72 17 0 10 Jan 2018
Finite Sample Differentially Private Confidence Intervals Vishesh Karwa Salil P. Vadhan 52 193 0 10 Nov 2017
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 68 823 0 06 May 2016
Algorithms for Differentially Private Multi-Armed Bandits Aristide C. Y. Tossou Christos Dimitrakakis FedML 56 111 0 27 Nov 2015
Cascading Bandits: Learning to Rank in the Cascade Model Branislav Kveton Csaba Szepesvári Zheng Wen Azin Ashkan 134 284 0 10 Feb 2015
Bounded regret in stochastic multi-armed bandits Sébastien Bubeck Vianney Perchet Philippe Rigollet 154 92 0 06 Feb 2013
Portfolio Allocation for Bayesian Optimization E. Brochu Matthew W. Hoffman Nando de Freitas 384 279 0 28 Sep 2010