Copertina

From Restless to Contextual: A Thresholding Bandit Reformulation For Finite-horizon Improvement

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xu, Jiamin, Nazarov, Ivan, Rastogi, Aditya, Periáñez, África, Gan, Kyra
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Fast Non-Episodic Finite-Horizon RL with K-Step Lookahead Thresholding
di: Xu, Jiamin, et al.
Pubblicazione: (2026)

The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems
di: Periáñez, África, et al.
Pubblicazione: (2024)

Adaptive User Journeys in Pharma E-Commerce with Reinforcement Learning: Insights from SwipeRx
di: del Río, Ana Fernández, et al.
Pubblicazione: (2024)

Contextual Bandits with Budgeted Information Reveal
di: Gan, Kyra, et al.
Pubblicazione: (2023)

Optimizing HIV Patient Engagement with Reinforcement Learning in Resource-Limited Settings
di: Periáñez, África, et al.
Pubblicazione: (2024)

Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services
di: del Río, Ana Fernández, et al.
Pubblicazione: (2024)

Integrating Causal DAGs in Deep RL: Activating Minimal Markovian States with Multi-Order Exposure
di: Xu, Jiamin, et al.
Pubblicazione: (2026)

MultiScale Contextual Bandits for Long Term Objectives
di: Rastogi, Richa, et al.
Pubblicazione: (2025)

Restless Linear Bandits
di: Khaleghi, Azadeh
Pubblicazione: (2024)

The Bandit Whisperer: Communication Learning for Restless Bandits
di: Zhao, Yunfan, et al.
Pubblicazione: (2024)

CSPI-MT: Calibrated Safe Policy Improvement with Multiple Testing for Threshold Policies
di: Cho, Brian M, et al.
Pubblicazione: (2024)

Data-Driven Approach to Capitation Reform in Rwanda
di: Olaniyi, Babaniyi, et al.
Pubblicazione: (2025)

Fairness of Exposure in Online Restless Multi-armed Bandits
di: Sood, Archit, et al.
Pubblicazione: (2024)

Finite-Horizon Single-Pull Restless Bandits: An Efficient Index Policy For Scarce Resource Allocation
di: Xiong, Guojun, et al.
Pubblicazione: (2025)

Faster Q-Learning Algorithms for Restless Bandits
di: Kakarapalli, Parvish, et al.
Pubblicazione: (2024)

A Modularized Framework for Piecewise-Stationary Restless Bandits
di: Li, Kuan-Ta, et al.
Pubblicazione: (2026)

Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits
di: Cho, Brian, et al.
Pubblicazione: (2024)

MARBLE: Multi-Armed Restless Bandits in Latent Markovian Environment
di: Amiri, Mohsen, et al.
Pubblicazione: (2025)

Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee
di: Hung, Yu-Heng, et al.
Pubblicazione: (2025)

Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting
di: Genalti, Gianmarco, et al.
Pubblicazione: (2024)

General Formulation and PCL-Analysis for Restless Bandits with Limited Observability
di: Liu, Keqin, et al.
Pubblicazione: (2023)

Networked Restless Multi-Arm Bandits with Reinforcement Learning
di: Zhang, Hanmo, et al.
Pubblicazione: (2025)

Low-Complexity Algorithm for Restless Bandits with Imperfect Observations
di: Liu, Keqin, et al.
Pubblicazione: (2021)

Global Rewards in Restless Multi-Armed Bandits
di: Raman, Naveen, et al.
Pubblicazione: (2024)

Context in Public Health for Underserved Communities: A Bayesian Approach to Online Restless Bandits
di: Liang, Biyonka, et al.
Pubblicazione: (2024)

IRL for Restless Multi-Armed Bandits with Applications in Maternal and Child Health
di: Jain, Gauri, et al.
Pubblicazione: (2024)

Neural Index Policies for Restless Multi-Action Bandits with Heterogeneous Budgets
di: Pandey, Himadri S., et al.
Pubblicazione: (2025)

Model Predictive Control is Almost Optimal for Restless Bandit
di: Gast, Nicolas, et al.
Pubblicazione: (2024)

Optimal Best Arm Identification with Fixed Confidence in Restless Bandits
di: Karthik, P. N., et al.
Pubblicazione: (2023)

Whittle Index Learning Algorithms for Restless Bandits with Constant Stepsizes
di: Mittal, Vishesh, et al.
Pubblicazione: (2024)

A Federated Online Restless Bandit Framework for Cooperative Resource Allocation
di: Tong, Jingwen, et al.
Pubblicazione: (2024)

Optimal Control of Fluid Restless Multi-armed Bandits: A Machine Learning Approach
di: Bertsimas, Dimitris, et al.
Pubblicazione: (2025)

Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels
di: Shisher, Md Kamran Chowdhury, et al.
Pubblicazione: (2025)

Linear Contextual Bandits with Interference
di: Xu, Yang, et al.
Pubblicazione: (2024)

Lagrangian Index Policy for Restless Bandits with Average Reward
di: Avrachenkov, Konstantin, et al.
Pubblicazione: (2024)

DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback
di: Xiong, Guojun, et al.
Pubblicazione: (2024)

Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback
di: Xiong, Guojun, et al.
Pubblicazione: (2024)

Distributed Learning in Markovian Restless Bandits over Interference Graphs for Stable Spectrum Sharing
di: Didi, Liad Lea, et al.
Pubblicazione: (2025)

GINO-Q: Learning an Asymptotically Optimal Index Policy for Restless Multi-armed Bandits
di: Chen, Gongpu, et al.
Pubblicazione: (2024)

Restless Bandits with Individual Penalty Constraints: Near-Optimal Indices and Deep Reinforcement Learning
di: Zamir, Nida, et al.
Pubblicazione: (2026)