Imagen de Portada

Clus-UCB: A Near-Optimal Algorithm for Clustered Bandits

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gore, Aakash, Chaporkar, Prasanna
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Threshold-Based Optimal Arm Selection in Monotonic Bandits: Regret Lower Bounds and Algorithms
por: Varude, Chanakya, et al.
Publicado: (2025)

Revisiting Social Welfare in Bandits: UCB is (Nearly) All You Need
por: Sarkar, Dhruv, et al.
Publicado: (2025)

Replicable Bandits with UCB based Exploration
por: Deb, Rohan, et al.
Publicado: (2026)

Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms
por: Rezaei, Parham, et al.
Publicado: (2024)

A UCB Bandit Algorithm for General ML-Based Estimators
por: Liu, Yajing, et al.
Publicado: (2026)

Cooperative Multi-Agent Graph Bandits: UCB Algorithm and Regret Analysis
por: Paschalidis, Phevos, et al.
Publicado: (2024)

Nearly-Optimal Algorithm for Adversarial Kernelized Bandits
por: Iwazaki, Shogo
Publicado: (2026)

Near-Optimal Algorithm for Non-Stationary Kernelized Bandits
por: Iwazaki, Shogo, et al.
Publicado: (2024)

Truncated LinUCB for Stochastic Linear Bandits
por: Song, Yanglei, et al.
Publicado: (2022)

Near Optimal Best Arm Identification for Clustered Bandits
por: Yash, et al.
Publicado: (2025)

Extended UCB Policies for Multi-armed Bandit Problems
por: Liu, Keqin, et al.
Publicado: (2011)

Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback
por: Di, Qiwei, et al.
Publicado: (2024)

Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
por: Bui, Ha Manh, et al.
Publicado: (2024)

InfoClus: Informative Clustering of High-dimensional Data Embeddings
por: Lai, Fuyin, et al.
Publicado: (2025)

Near-Optimal Regret in Adversarial Kernel Bandits
por: Zhang, Yu-Jie, et al.
Publicado: (2026)

Near Optimal Pure Exploration in Logistic Bandits
por: Rivera, Eduardo Ochoa, et al.
Publicado: (2024)

Optimal Clustering with Bandit Feedback
por: Yang, Junwen, et al.
Publicado: (2022)

Nearly Minimax Optimal Submodular Maximization with Bandit Feedback
por: Tajdini, Artin, et al.
Publicado: (2023)

Nearly Minimax Optimal Regret for Multinomial Logistic Bandit
por: Lee, Joongkyu, et al.
Publicado: (2024)

PAK-UCB Contextual Bandit: An Online Learning Approach to Prompt-Aware Selection of Generative Models and LLMs
por: Hu, Xiaoyan, et al.
Publicado: (2024)

UCB-type Algorithm for Budget-Constrained Expert Learning
por: Latypov, Ilgam, et al.
Publicado: (2025)

Optimal and Practical Batched Linear Bandit Algorithm
por: Yu, Sanghoon, et al.
Publicado: (2025)

Linear Bandits on Ellipsoids: Minimax Optimal Algorithms
por: Zhang, Raymond, et al.
Publicado: (2025)

Optimal Streaming Algorithms for Multi-Armed Bandits
por: Jin, Tianyuan, et al.
Publicado: (2024)

Nearly Optimal Best Arm Identification for Semiparametric Bandits
por: Kim, Seok-Jin
Publicado: (2026)

Uncertainty-Aware Dual-Student Knowledge Distillation for Efficient Image Classification
por: Gore, Aakash, et al.
Publicado: (2025)

Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
por: Cassel, Asaf, et al.
Publicado: (2024)

Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
por: Huang, Ruiquan, et al.
Publicado: (2023)

Near-Optimal Regret for Distributed Adversarial Bandits: A Black-Box Approach
por: Qiu, Hao, et al.
Publicado: (2026)

Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses
por: Zuo, Shiliang
Publicado: (2020)

Optimal Arm Elimination Algorithms for Combinatorial Bandits
por: Wen, Yuxiao, et al.
Publicado: (2025)

Preference-centric Bandits: Optimality of Mixtures and Regret-efficient Algorithms
por: Tatlı, Meltem, et al.
Publicado: (2025)

Near-Optimality of Contrastive Divergence Algorithms
por: Glaser, Pierre, et al.
Publicado: (2025)

Near-Optimal Regret for Efficient Stochastic Combinatorial Semi-Bandits
por: Ye, Zichun, et al.
Publicado: (2025)

Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms
por: Réveillard, William, et al.
Publicado: (2025)

Empirical Comparison of Forgetting Mechanisms for UCB-based Algorithms on a Data-Driven Simulation Platform
por: Chen, Minxin
Publicado: (2025)

Near-Optimal Algorithms for Constrained k-Center Clustering with Instance-level Background Knowledge
por: Guo, Longkun, et al.
Publicado: (2024)

Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits
por: Tamás, Ambrus, et al.
Publicado: (2024)

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

Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithms
por: Tatlı, Meltem, et al.
Publicado: (2025)