Locally Differentially Private Thresholding Bandits
Fuente:
arXiv
Saved in:
| Main Authors: | Barbara, Annalisa, Lazzaro, Joseph, Pike-Burke, Ciara |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Fixed-Budget Change Point Identification in Piecewise Constant Bandits
by: Lazzaro, Joseph, et al.
Published: (2025)
by: Lazzaro, Joseph, et al.
Published: (2025)
Fixed-Confidence Multiple Change Point Identification under Bandit Feedback
by: Lazzaro, Joseph, et al.
Published: (2025)
by: Lazzaro, Joseph, et al.
Published: (2025)
QuACK: A Multipurpose Queuing Algorithm for Cooperative $k$-Armed Bandits
by: Howson, Benjamin, et al.
Published: (2024)
by: Howson, Benjamin, et al.
Published: (2024)
When and why randomised exploration works (in linear bandits)
by: Abeille, Marc, et al.
Published: (2025)
by: Abeille, Marc, et al.
Published: (2025)
Learning Fair And Effective Points-Based Rewards Programs
by: Hssaine, Chamsi, et al.
Published: (2025)
by: Hssaine, Chamsi, et al.
Published: (2025)
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
by: Johnson, Emmeran, et al.
Published: (2023)
by: Johnson, Emmeran, et al.
Published: (2023)
Stochastic Shortest Path with Sparse Adversarial Costs
by: Johnson, Emmeran, et al.
Published: (2025)
by: Johnson, Emmeran, et al.
Published: (2025)
On the necessity of adaptive regularisation:Optimal anytime online learning on $\boldsymbol{\ell_p}$-balls
by: Johnson, Emmeran, et al.
Published: (2025)
by: Johnson, Emmeran, et al.
Published: (2025)
Differentially Private Kernelized Contextual Bandits
by: Pavlovic, Nikola, et al.
Published: (2025)
by: Pavlovic, Nikola, et al.
Published: (2025)
Differentially Private Release and Learning of Threshold Functions
by: Bun, Mark, et al.
Published: (2015)
by: Bun, Mark, et al.
Published: (2015)
KL-regularization Itself is Differentially Private in Bandits and RLHF
by: Zhang, Yizhou, et al.
Published: (2025)
by: Zhang, Yizhou, et al.
Published: (2025)
Differentially Private High Dimensional Bandits
by: Shukla, Apurv
Published: (2024)
by: Shukla, Apurv
Published: (2024)
Locally Private Nonparametric Contextual Multi-armed Bandits
by: Ma, Yuheng, et al.
Published: (2025)
by: Ma, Yuheng, et al.
Published: (2025)
Optimal Thresholding Linear Bandit
by: Rivera, Eduardo Ochoa, et al.
Published: (2024)
by: Rivera, Eduardo Ochoa, et al.
Published: (2024)
On the Optimal Regret of Locally Private Linear Contextual Bandit
by: Li, Jiachun, et al.
Published: (2024)
by: Li, Jiachun, et al.
Published: (2024)
Differentially Private Linear Bandits with Partial Distributed Feedback
by: Li, Fengjiao, et al.
Published: (2022)
by: Li, Fengjiao, et al.
Published: (2022)
Faster Rates for Private Adversarial Bandits
by: Asi, Hilal, et al.
Published: (2025)
by: Asi, Hilal, et al.
Published: (2025)
Differentially Private Hyperparameter Tuning using Local Bayesian Optimization
by: Sopa, Getoar, et al.
Published: (2025)
by: Sopa, Getoar, et al.
Published: (2025)
Exactly Minimax-Optimal Locally Differentially Private Sampling
by: Park, Hyun-Young, et al.
Published: (2024)
by: Park, Hyun-Young, et al.
Published: (2024)
Contraction of Locally Differentially Private Mechanisms
by: Asoodeh, Shahab, et al.
Published: (2022)
by: Asoodeh, Shahab, et al.
Published: (2022)
From Restless to Contextual: A Thresholding Bandit Reformulation For Finite-horizon Improvement
by: Xu, Jiamin, et al.
Published: (2025)
by: Xu, Jiamin, et al.
Published: (2025)
LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem
by: Wu, Yun-Ang, et al.
Published: (2024)
by: Wu, Yun-Ang, et al.
Published: (2024)
Strategic Incentivization for Locally Differentially Private Federated Learning
by: Pagoti, Yashwant Krishna, et al.
Published: (2025)
by: Pagoti, Yashwant Krishna, et al.
Published: (2025)
Differentially Private Wasserstein Barycenters
by: Gu, Anming, et al.
Published: (2025)
by: Gu, Anming, et al.
Published: (2025)
Differentially Private Policy Gradient
by: Rio, Alexandre, et al.
Published: (2025)
by: Rio, Alexandre, et al.
Published: (2025)
Differentially Private Geodesic Regression
by: Kulkarni, Aditya, et al.
Published: (2025)
by: Kulkarni, Aditya, et al.
Published: (2025)
Differentially Private Conformal Prediction
by: Wu, Jiamei, et al.
Published: (2026)
by: Wu, Jiamei, et al.
Published: (2026)
Data Poisoning Attacks to Locally Differentially Private Range Query Protocols
by: Liao, Ting-Wei, et al.
Published: (2025)
by: Liao, Ting-Wei, et al.
Published: (2025)
Locally Differentially Private Embedding Models in Distributed Fraud Prevention Systems
by: Perez, Iker, et al.
Published: (2024)
by: Perez, Iker, et al.
Published: (2024)
ALI-DPFL: Differentially Private Federated Learning with Adaptive Local Iterations
by: Ling, Xinpeng, et al.
Published: (2023)
by: Ling, Xinpeng, et al.
Published: (2023)
Threshold-Based Optimal Arm Selection in Monotonic Bandits: Regret Lower Bounds and Algorithms
by: Varude, Chanakya, et al.
Published: (2025)
by: Varude, Chanakya, et al.
Published: (2025)
Thresholding Data Shapley for Data Cleansing Using Multi-Armed Bandits
by: Namba, Hiroyuki, et al.
Published: (2024)
by: Namba, Hiroyuki, et al.
Published: (2024)
A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback
by: Lazzaro, Joseph, et al.
Published: (2026)
by: Lazzaro, Joseph, et al.
Published: (2026)
Locally Differentially Private Online Federated Learning With Correlated Noise
by: Zhang, Jiaojiao, et al.
Published: (2024)
by: Zhang, Jiaojiao, et al.
Published: (2024)
Locally Differentially Private Distributed Online Learning with Guaranteed Optimality
by: Chen, Ziqin, et al.
Published: (2023)
by: Chen, Ziqin, et al.
Published: (2023)
On Using Secure Aggregation in Differentially Private Federated Learning with Multiple Local Steps
by: Heikkilä, Mikko A.
Published: (2024)
by: Heikkilä, Mikko A.
Published: (2024)
Decentralized Differentially Private Power Method
by: Campbell, Andrew, et al.
Published: (2025)
by: Campbell, Andrew, et al.
Published: (2025)
Offline Local Search for Online Stochastic Bandits
by: Benadè, Gerdus, et al.
Published: (2026)
by: Benadè, Gerdus, et al.
Published: (2026)
Private and Fair Machine Learning: Revisiting the Disparate Impact of Differentially Private SGD
by: Demelius, Lea, et al.
Published: (2025)
by: Demelius, Lea, et al.
Published: (2025)
Shuffle and Joint Differential Privacy for Generalized Linear Contextual Bandits
by: Sarmasarkar, Sahasrajit
Published: (2026)
by: Sarmasarkar, Sahasrajit
Published: (2026)
Similar Items
-
Fixed-Budget Change Point Identification in Piecewise Constant Bandits
by: Lazzaro, Joseph, et al.
Published: (2025) -
Fixed-Confidence Multiple Change Point Identification under Bandit Feedback
by: Lazzaro, Joseph, et al.
Published: (2025) -
QuACK: A Multipurpose Queuing Algorithm for Cooperative $k$-Armed Bandits
by: Howson, Benjamin, et al.
Published: (2024) -
When and why randomised exploration works (in linear bandits)
by: Abeille, Marc, et al.
Published: (2025) -
Learning Fair And Effective Points-Based Rewards Programs
by: Hssaine, Chamsi, et al.
Published: (2025)