Saved in:
| Main Authors: | Zamir, Nida, Hou, I-Hong |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.04101 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Deep Index Policy for Multi-Resource Restless Matching Bandit and Its Application in Multi-Channel Scheduling
by: Zamir, Nida, et al.
Published: (2024)
by: Zamir, Nida, et al.
Published: (2024)
Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels
by: Shisher, Md Kamran Chowdhury, et al.
Published: (2025)
by: Shisher, Md Kamran Chowdhury, et al.
Published: (2025)
Networked Restless Multi-Arm Bandits with Reinforcement Learning
by: Zhang, Hanmo, et al.
Published: (2025)
by: Zhang, Hanmo, et al.
Published: (2025)
The Bandit Whisperer: Communication Learning for Restless Bandits
by: Zhao, Yunfan, et al.
Published: (2024)
by: Zhao, Yunfan, et al.
Published: (2024)
Restless Linear Bandits
by: Khaleghi, Azadeh
Published: (2024)
by: Khaleghi, Azadeh
Published: (2024)
Model Predictive Control is Almost Optimal for Restless Bandit
by: Gast, Nicolas, et al.
Published: (2024)
by: Gast, Nicolas, et al.
Published: (2024)
Optimal Best Arm Identification with Fixed Confidence in Restless Bandits
by: Karthik, P. N., et al.
Published: (2023)
by: Karthik, P. N., et al.
Published: (2023)
GINO-Q: Learning an Asymptotically Optimal Index Policy for Restless Multi-armed Bandits
by: Chen, Gongpu, et al.
Published: (2024)
by: Chen, Gongpu, et al.
Published: (2024)
Optimal Control of Fluid Restless Multi-armed Bandits: A Machine Learning Approach
by: Bertsimas, Dimitris, et al.
Published: (2025)
by: Bertsimas, Dimitris, et al.
Published: (2025)
Faster Q-Learning Algorithms for Restless Bandits
by: Kakarapalli, Parvish, et al.
Published: (2024)
by: Kakarapalli, Parvish, et al.
Published: (2024)
Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback
by: Xiong, Guojun, et al.
Published: (2024)
by: Xiong, Guojun, et al.
Published: (2024)
Whittle Index Learning Algorithms for Restless Bandits with Constant Stepsizes
by: Mittal, Vishesh, et al.
Published: (2024)
by: Mittal, Vishesh, et al.
Published: (2024)
Model Predictive Control is almost Optimal for Heterogeneous Restless Multi-armed Bandits
by: Narasimha, Dheeraj, et al.
Published: (2025)
by: Narasimha, Dheeraj, et al.
Published: (2025)
Fairness of Exposure in Online Restless Multi-armed Bandits
by: Sood, Archit, et al.
Published: (2024)
by: Sood, Archit, et al.
Published: (2024)
Multi-Action Restless Bandits with Weakly Coupled Constraints: Simultaneous Learning and Control
by: Fu, Jing, et al.
Published: (2024)
by: Fu, Jing, et al.
Published: (2024)
DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback
by: Xiong, Guojun, et al.
Published: (2024)
by: Xiong, Guojun, et al.
Published: (2024)
Unichain and Aperiodicity are Sufficient for Asymptotic Optimality of Average-Reward Restless Bandits
by: Hong, Yige, et al.
Published: (2024)
by: Hong, Yige, et al.
Published: (2024)
Global Rewards in Restless Multi-Armed Bandits
by: Raman, Naveen, et al.
Published: (2024)
by: Raman, Naveen, et al.
Published: (2024)
Achieving Exponential Asymptotic Optimality in Average-Reward Restless Bandits without Global Attractor Assumption
by: Hong, Yige, et al.
Published: (2024)
by: Hong, Yige, et al.
Published: (2024)
A Modularized Framework for Piecewise-Stationary Restless Bandits
by: Li, Kuan-Ta, et al.
Published: (2026)
by: Li, Kuan-Ta, et al.
Published: (2026)
Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting
by: Genalti, Gianmarco, et al.
Published: (2024)
by: Genalti, Gianmarco, et al.
Published: (2024)
General Formulation and PCL-Analysis for Restless Bandits with Limited Observability
by: Liu, Keqin, et al.
Published: (2023)
by: Liu, Keqin, et al.
Published: (2023)
MARBLE: Multi-Armed Restless Bandits in Latent Markovian Environment
by: Amiri, Mohsen, et al.
Published: (2025)
by: Amiri, Mohsen, et al.
Published: (2025)
Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee
by: Hung, Yu-Heng, et al.
Published: (2025)
by: Hung, Yu-Heng, et al.
Published: (2025)
Low-Complexity Algorithm for Restless Bandits with Imperfect Observations
by: Liu, Keqin, et al.
Published: (2021)
by: Liu, Keqin, et al.
Published: (2021)
Position: Adopt Constraints Over Fixed Penalties in Deep Learning
by: Ramirez, Juan, et al.
Published: (2025)
by: Ramirez, Juan, et al.
Published: (2025)
Distributed No-Regret Learning for Multi-Stage Systems with End-to-End Bandit Feedback
by: Hou, I-Hong
Published: (2024)
by: Hou, I-Hong
Published: (2024)
Distributed Learning in Markovian Restless Bandits over Interference Graphs for Stable Spectrum Sharing
by: Didi, Liad Lea, et al.
Published: (2025)
by: Didi, Liad Lea, et al.
Published: (2025)
Risk-Aware Decision Making in Restless Bandits: Theory and Algorithms for Planning and Learning
by: Akbarzadeh, Nima, et al.
Published: (2024)
by: Akbarzadeh, Nima, et al.
Published: (2024)
Neural Index Policies for Restless Multi-Action Bandits with Heterogeneous Budgets
by: Pandey, Himadri S., et al.
Published: (2025)
by: Pandey, Himadri S., et al.
Published: (2025)
Lagrangian Index Policy for Restless Bandits with Average Reward
by: Avrachenkov, Konstantin, et al.
Published: (2024)
by: Avrachenkov, Konstantin, et al.
Published: (2024)
Nearly-Optimal Algorithm for Adversarial Kernelized Bandits
by: Iwazaki, Shogo
Published: (2026)
by: Iwazaki, Shogo
Published: (2026)
Near-Optimal Regret in Adversarial Kernel Bandits
by: Zhang, Yu-Jie, et al.
Published: (2026)
by: Zhang, Yu-Jie, et al.
Published: (2026)
Near Optimal Pure Exploration in Logistic Bandits
by: Rivera, Eduardo Ochoa, et al.
Published: (2024)
by: Rivera, Eduardo Ochoa, et al.
Published: (2024)
Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption
by: Hong, Yige, et al.
Published: (2023)
by: Hong, Yige, et al.
Published: (2023)
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)
IRL for Restless Multi-Armed Bandits with Applications in Maternal and Child Health
by: Jain, Gauri, et al.
Published: (2024)
by: Jain, Gauri, et al.
Published: (2024)
A Federated Online Restless Bandit Framework for Cooperative Resource Allocation
by: Tong, Jingwen, et al.
Published: (2024)
by: Tong, Jingwen, et al.
Published: (2024)
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
by: Qiao, Dan, et al.
Published: (2024)
by: Qiao, Dan, et al.
Published: (2024)
ContextWIN: Whittle Index Based Mixture-of-Experts Neural Model For Restless Bandits Via Deep RL
by: Guo, Zhanqiu, et al.
Published: (2024)
by: Guo, Zhanqiu, et al.
Published: (2024)
Similar Items
-
Deep Index Policy for Multi-Resource Restless Matching Bandit and Its Application in Multi-Channel Scheduling
by: Zamir, Nida, et al.
Published: (2024) -
Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels
by: Shisher, Md Kamran Chowdhury, et al.
Published: (2025) -
Networked Restless Multi-Arm Bandits with Reinforcement Learning
by: Zhang, Hanmo, et al.
Published: (2025) -
The Bandit Whisperer: Communication Learning for Restless Bandits
by: Zhao, Yunfan, et al.
Published: (2024) -
Restless Linear Bandits
by: Khaleghi, Azadeh
Published: (2024)