ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2207.03445
  4. Cited By
Differentially Private Stochastic Linear Bandits: (Almost) for Free

Differentially Private Stochastic Linear Bandits: (Almost) for Free

IEEE Journal on Selected Areas in Information Theory (JSAIT), 2022
7 July 2022
Osama A. Hanna
Antonious M. Girgis
Christina Fragouli
Suhas Diggavi
    FedML
ArXiv (abs)PDFHTML

Papers citing "Differentially Private Stochastic Linear Bandits: (Almost) for Free"

14 / 14 papers shown
Beyond ATE: Multi-Criteria Design for A/B Testing
Beyond ATE: Multi-Criteria Design for A/B Testing
Jiachun Li
Kaining Shi
David Simchi-Levi
149
0
0
06 Sep 2025
Does Feedback Help in Bandits with Arm Erasures?
Does Feedback Help in Bandits with Arm Erasures?International Symposium on Information Theory (ISIT), 2025
Merve Karakas
Osama A. Hanna
Lin Yang
Christina Fragouli
272
0
0
29 Apr 2025
The Safety-Privacy Tradeoff in Linear Bandits
The Safety-Privacy Tradeoff in Linear BanditsInternational Symposium on Information Theory (ISIT), 2025
Arghavan Zibaie
Spencer Hutchinson
Ramtin Pedarsani
Mahnoosh Alizadeh
232
0
0
23 Apr 2025
Differentially Private Kernelized Contextual Bandits
Differentially Private Kernelized Contextual BanditsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Nikola Pavlovic
Sudeep Salgia
Qing Zhao
310
3
0
13 Jan 2025
Federated Online Prediction from Experts with Differential Privacy:
  Separations and Regret Speed-ups
Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-upsNeural Information Processing Systems (NeurIPS), 2024
Fengyu Gao
Ruiquan Huang
Jing Yang
FedML
221
1
0
27 Sep 2024
FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear
  Bandits
FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits
Sunrit Chakraborty
Saptarshi Roy
Debabrota Basu
FedML
508
1
0
22 May 2024
On the Optimal Regret of Locally Private Linear Contextual Bandit
On the Optimal Regret of Locally Private Linear Contextual Bandit
Jiachun Li
David Simchi-Levi
Yining Wang
237
2
0
15 Apr 2024
Differentially Private High Dimensional Bandits
Differentially Private High Dimensional Bandits
Apurv Shukla
244
0
0
06 Feb 2024
Fixed-Budget Differentially Private Best Arm Identification
Fixed-Budget Differentially Private Best Arm IdentificationInternational Conference on Learning Representations (ICLR), 2024
Zhirui Chen
P. Karthik
Yeow Meng Chee
Vincent Y. F. Tan
240
2
0
17 Jan 2024
Privacy Preserving Adaptive Experiment Design
Privacy Preserving Adaptive Experiment DesignInternational Conference on Machine Learning (ICML), 2024
Jiachun Li
Kaining Shi
David Simchi-Levi
521
1
0
16 Jan 2024
Concentrated Differential Privacy for Bandits
Concentrated Differential Privacy for Bandits
Achraf Azize
D. Basu
425
9
0
01 Sep 2023
Federated Linear Contextual Bandits with User-level Differential Privacy
Federated Linear Contextual Bandits with User-level Differential PrivacyInternational Conference on Machine Learning (ICML), 2023
Ruiquan Huang
Huanyu Zhang
Luca Melis
Milan Shen
Meisam Hajzinia
J. Yang
FedML
364
17
0
08 Jun 2023
Robust and differentially private stochastic linear bandits
Robust and differentially private stochastic linear bandits
Vasileios Charisopoulos
Hossein Esfandiari
Vahab Mirrokni
FedML
265
1
0
23 Apr 2023
On Differentially Private Federated Linear Contextual Bandits
On Differentially Private Federated Linear Contextual BanditsInternational Conference on Learning Representations (ICLR), 2023
Xingyu Zhou
Sayak Ray Chowdhury
FedML
472
16
0
27 Feb 2023
1
Page 1 of 1