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2006.00701
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Locally Differentially Private (Contextual) Bandits Learning
Neural Information Processing Systems (NeurIPS), 2020
1 June 2020
Kai Zheng
Tianle Cai
Weiran Huang
Zhenguo Li
Liwei Wang
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Papers citing
"Locally Differentially Private (Contextual) Bandits Learning"
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KL-regularization Itself is Differentially Private in Bandits and RLHF
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The Safety-Privacy Tradeoff in Linear Bandits
International Symposium on Information Theory (ISIT), 2025
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Locally Private Nonparametric Contextual Multi-armed Bandits
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Beyond Covariance Matrix: The Statistical Complexity of Private Linear Regression
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438
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Differentially Private Kernelized Contextual Bandits
International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Nikola Pavlovic
Sudeep Salgia
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303
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Private Selection with Heterogeneous Sensitivities
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293
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Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups
Neural Information Processing Systems (NeurIPS), 2024
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Privacy Preserving Reinforcement Learning for Population Processes
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247
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FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits
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505
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234
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Fixed-Budget Differentially Private Best Arm Identification
International Conference on Learning Representations (ICLR), 2024
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234
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Privacy Preserving Adaptive Experiment Design
International Conference on Machine Learning (ICML), 2024
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Kaining Shi
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520
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DPMAC: Differentially Private Communication for Cooperative Multi-Agent Reinforcement Learning
International Joint Conference on Artificial Intelligence (IJCAI), 2023
Canzhe Zhao
Yanjie Ze
Jing Dong
Baoxiang Wang
Shuai Li
281
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Federated Linear Contextual Bandits with User-level Differential Privacy
International Conference on Machine Learning (ICML), 2023
Ruiquan Huang
Huanyu Zhang
Luca Melis
Milan Shen
Meisam Hajzinia
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361
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Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
International Conference on Machine Learning (ICML), 2023
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Xingyu Zhou
Sayak Ray Chowdhury
Haiyan Zhao
416
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Robust and differentially private stochastic linear bandits
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Hossein Esfandiari
Vahab Mirrokni
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264
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Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles
International Conference on Learning Representations (ICLR), 2023
Zhiwei Tang
Dmitry Rybin
Tsung-Hui Chang
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558
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On Differentially Private Federated Linear Contextual Bandits
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Xingyu Zhou
Sayak Ray Chowdhury
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466
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Concurrent Shuffle Differential Privacy Under Continual Observation
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Haim Kaplan
Yishay Mansour
Uri Stemmer
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297
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Local Differential Privacy for Sequential Decision Making in a Changing Environment
Pratik Gajane
198
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Near-Optimal Differentially Private Reinforcement Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Dan Qiao
Yu Wang
364
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Vertical Federated Linear Contextual Bandits
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Zhipeng Liang
Shu Zhen Zhang
Hang Li
Ouyang Wen
Yu Rong
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Bing Wu
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227
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20 Oct 2022
When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits
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Achraf Azize
D. Basu
333
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Federated Online Clustering of Bandits
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Xutong Liu
Haoruo Zhao
Tong Yu
Shuai Li
John C. S. Lui
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250
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31 Aug 2022
Dynamic Global Sensitivity for Differentially Private Contextual Bandits
ACM Conference on Recommender Systems (RecSys), 2022
Huazheng Wang
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Hongning Wang
297
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Differentially Private Linear Bandits with Partial Distributed Feedback
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Bo Ji
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297
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Differentially Private Stochastic Linear Bandits: (Almost) for Free
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Osama A. Hanna
Antonious M. Girgis
Christina Fragouli
Suhas Diggavi
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385
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07 Jul 2022
Distributed Differential Privacy in Multi-Armed Bandits
International Conference on Learning Representations (ICLR), 2022
Sayak Ray Chowdhury
Xingyu Zhou
400
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Learning in Distributed Contextual Linear Bandits Without Sharing the Context
Osama A. Hanna
Lin F. Yang
Christina Fragouli
FedML
208
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08 Jun 2022
Offline Reinforcement Learning with Differential Privacy
Neural Information Processing Systems (NeurIPS), 2022
Dan Qiao
Yu Wang
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433
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Shuffle Private Linear Contextual Bandits
International Conference on Machine Learning (ICML), 2022
Sayak Ray Chowdhury
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359
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Differentially Private Reinforcement Learning with Linear Function Approximation
Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2022
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327
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Differentially Private Regret Minimization in Episodic Markov Decision Processes
AAAI Conference on Artificial Intelligence (AAAI), 2021
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250
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Privacy Amplification via Shuffling for Linear Contextual Bandits
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Vianney Perchet
Matteo Pirotta
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378
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Differentially Private Exploration in Reinforcement Learning with Linear Representation
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Evrard Garcelon
A. Lazaric
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403
12
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Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes
Chonghua Liao
Jiafan He
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242
19
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19 Oct 2021
Differential Privacy in Personalized Pricing with Nonparametric Demand Models
Operational Research (OR), 2021
Xi Chen
Sentao Miao
Yining Wang
203
38
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10 Sep 2021
Optimal Order Simple Regret for Gaussian Process Bandits
Sattar Vakili
N. Bouziani
Sepehr Jalali
A. Bernacchia
Da-shan Shiu
268
61
0
20 Aug 2021
Large Scale Private Learning via Low-rank Reparametrization
International Conference on Machine Learning (ICML), 2021
Da Yu
Huishuai Zhang
Wei Chen
Jian Yin
Tie-Yan Liu
440
121
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17 Jun 2021
Differentially Private Multi-Armed Bandits in the Shuffle Model
Neural Information Processing Systems (NeurIPS), 2021
J. Tenenbaum
Haim Kaplan
Yishay Mansour
Uri Stemmer
FedML
219
34
0
05 Jun 2021
Encrypted Linear Contextual Bandit
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Evrard Garcelon
Vianney Perchet
Matteo Pirotta
FedML
227
2
0
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Local Differential Privacy for Regret Minimization in Reinforcement Learning
Evrard Garcelon
Vianney Perchet
Ciara Pike-Burke
Matteo Pirotta
378
42
0
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Local Differential Privacy for Bayesian Optimization
Xingyu Zhou
Jian Tan
258
28
0
13 Oct 2020
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning
Management Sciences (MS), 2020
Xi Chen
D. Simchi-Levi
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350
74
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Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles
Jung-hun Kim
Se-Young Yun
Minchan Jeong
J. Nam
Jinwoo Shin
Richard Combes
356
8
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03 Mar 2017
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