Imagen de Portada

Adaptive Sample Sharing for Multi Agent Linear Bandits

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Cherkaoui, Hamza, Barlier, Merwan, Colin, Igor
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Differentially Private Policy Gradient
por: Rio, Alexandre, et al.
Publicado: (2025)

Differentially Private Deep Model-Based Reinforcement Learning
por: Rio, Alexandre, et al.
Publicado: (2024)

Enhancing Reinforcement Learning Agents with Local Guides
por: Daoudi, Paul, et al.
Publicado: (2024)

When to Transfer: Adaptive Source Selection for Positive Transfer in Linear Models
por: Cherkaoui, Hamza, et al.
Publicado: (2025)

A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning
por: Daoudi, Paul, et al.
Publicado: (2023)

Learning Shared Representations for Multi-Task Linear Bandits
por: Lin, Jiabin, et al.
Publicado: (2026)

Improving a Proportional Integral Controller with Reinforcement Learning on a Throttle Valve Benchmark
por: Daoudi, Paul, et al.
Publicado: (2024)

Thompson Sampling for Multi-Objective Linear Contextual Bandit
por: Park, Somangchan, et al.
Publicado: (2025)

TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
por: Paolo, Giuseppe, et al.
Publicado: (2025)

Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training
por: Cherkaoui, Hamza, et al.
Publicado: (2026)

Generalized Linear Bandits with Limited Adaptivity
por: Sawarni, Ayush, et al.
Publicado: (2024)

Multi-Agent Stage-wise Conservative Linear Bandits
por: Afsharrad, Amirhossein, et al.
Publicado: (2025)

Cooperative Multi-Agent Constrained Stochastic Linear Bandits
por: Afsharrad, Amirhossein, et al.
Publicado: (2024)

Sparsity-Agnostic Linear Bandits with Adaptive Adversaries
por: Jin, Tianyuan, et al.
Publicado: (2024)

Efficient and Adaptive Posterior Sampling Algorithms for Bandits
por: Hu, Bingshan, et al.
Publicado: (2024)

Multi-Agent Lipschitz Bandits
por: Chakraborty, Sourav, et al.
Publicado: (2026)

Human in the Loop Adaptive Optimization for Improved Time Series Forecasting
por: Tiomoko, Malik, et al.
Publicado: (2025)

Adaptive Endpointing with Deep Contextual Multi-armed Bandits
por: Min, Do June, et al.
Publicado: (2023)

LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem
por: Wu, Yun-Ang, et al.
Publicado: (2024)

Learning with Limited Shared Information in Multi-agent Multi-armed Bandit
por: Shao, Junning, et al.
Publicado: (2025)

On the Power of Adaptivity for $\varepsilon$-Best Arm Identification in Linear Bandits
por: Maiti, Arnab, et al.
Publicado: (2026)

Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
por: Sandberg, Jack, et al.
Publicado: (2025)

Multi-Task Representation Learning for Conservative Linear Bandits
por: Lin, Jiabin, et al.
Publicado: (2026)

Multi-Agent Best Arm Identification in Stochastic Linear Bandits
por: Agrawal, Sanjana, et al.
Publicado: (2024)

Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
por: Jun, Kwang-Sung, et al.
Publicado: (2024)

Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals
por: Liu, Ziyi, et al.
Publicado: (2024)

Collaborating in Multi-Armed Bandits with Strategic Agents
por: Barnea, Idan, et al.
Publicado: (2026)

Blessings of Multiple Good Arms in Multi-Objective Linear Bandits
por: Ann, Heesang, et al.
Publicado: (2026)

Distributed Algorithms for Multi-Agent Multi-Armed Bandits with Collision
por: Zhou, Daoyuan, et al.
Publicado: (2025)

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
por: Zhao, Boxin, et al.
Publicado: (2021)

Transfer in Sequential Multi-armed Bandits via Reward Samples
por: R, Rahul N, et al.
Publicado: (2024)

HR-Bandit: Human-AI Collaborated Linear Recourse Bandit
por: Cao, Junyu, et al.
Publicado: (2024)

Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits
por: Huang, Ziyi, et al.
Publicado: (2024)

Infrequent Exploration in Linear Bandits
por: Lee, Harin, et al.
Publicado: (2025)

Optimal Thresholding Linear Bandit
por: Rivera, Eduardo Ochoa, et al.
Publicado: (2024)

Federated Linear Dueling Bandits
por: Huang, Xuhan, et al.
Publicado: (2025)

Multi-Agent Stochastic Bandits Robust to Adversarial Corruptions
por: Ghaffari, Fatemeh, et al.
Publicado: (2024)

Bandit Pareto Set Identification in a Multi-Output Linear Model
por: Kone, Cyrille, et al.
Publicado: (2025)

Towards Noise-Resilient Quantum Multi-Armed and Stochastic Linear Bandits
por: Chen, Zhuoyue, et al.
Publicado: (2026)

Restless Linear Bandits
por: Khaleghi, Azadeh
Publicado: (2024)