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Differentially Private Stochastic Linear Bandits: (Almost) for Free

Differentially Private Stochastic Linear Bandits: (Almost) for Free

Osama A. Hanna
Antonious M. Girgis
Christina Fragouli
Suhas Diggavi
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Papers citing "Differentially Private Stochastic Linear Bandits: (Almost) for Free"

7 / 7 papers shown
Title
Differentially Private Linear Bandits with Partial Distributed Feedback
Differentially Private Linear Bandits with Partial Distributed Feedback
Fengjiao Li
Xingyu Zhou
Bo Ji
FedML
46
14
0
12 Jul 2022
Privacy Amplification via Shuffling for Linear Contextual Bandits
Privacy Amplification via Shuffling for Linear Contextual Bandits
Evrard Garcelon
Kamalika Chaudhuri
Vianney Perchet
Matteo Pirotta
FedML
76
19
0
11 Dec 2021
Differentially Private Multi-Armed Bandits in the Shuffle Model
Differentially Private Multi-Armed Bandits in the Shuffle Model
J. Tenenbaum
Haim Kaplan
Yishay Mansour
Uri Stemmer
FedML
51
29
0
05 Jun 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling
Vitaly Feldman
Audra McMillan
Kunal Talwar
FedML
61
161
0
23 Dec 2020
Multi-Armed Bandits with Local Differential Privacy
Multi-Armed Bandits with Local Differential Privacy
Wenbo Ren
Xingyu Zhou
Jia Liu
Ness B. Shroff
24
48
0
06 Jul 2020
An Optimal Private Stochastic-MAB Algorithm Based on an Optimal Private Stopping Rule
An Optimal Private Stochastic-MAB Algorithm Based on an Optimal Private Stopping Rule
Touqir Sajed
Or Sheffet
48
48
0
22 May 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
Ulfar Erlingsson
Vitaly Feldman
Ilya Mironov
A. Raghunathan
Kunal Talwar
Abhradeep Thakurta
172
426
0
29 Nov 2018