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Multi-Armed Bandits

1044 directly classified papers

Papers per year

Papers

Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025
Stochastic Online Instrumental Variable Regression: Regrets for Endogeneity and Bandit Feedback AAAI 2025
Forecasting Competitions with Correlated Events AAAI 2025
Adapting to Non-Stationary Environments: Multi-Armed Bandit Enhanced Retrieval-Augmented Generation on Knowledge Graphs AAAI 2025
In-Domain African Languages Translation Using LLMs and Multi-armed Bandits ACL 2025
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs JMLR 2025
Contextual Bandits with Stage-wise Constraints JMLR 2025
Multi-Objective Neural Bandits with Random Scalarization IJCAI 2025
Problem-dependent Regret for Lexicographic Multi-Armed Bandits with Adversarial Corruptions IJCAI 2025
Public Opinion Field Effect and Hawkes Process Join Hands for Information Popularity Prediction AAAI 2025
Robust Performance Incentivizing Algorithms for Multi-Armed Bandits with Strategic Agents AAAI 2025
Neural Combinatorial Clustered Bandits for Recommendation Systems AAAI 2025
Batch Ensemble for Variance Dependent Regret in Stochastic Bandits AAAI 2025
Improved Regret of Linear Ensemble Sampling NIPS 2024
Meta Learning in Bandits within shared affine Subspaces AISTATS 2024
Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication AISTATS 2024
Fast Rates for Bandit PAC Multiclass Classification NIPS 2024
Efficient Quantum Agnostic Improper Learning of Decision Trees AISTATS 2024
Federated Linear Contextual Bandits with Heterogeneous Clients AISTATS 2024
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates NIPS 2024
Improved Analysis for Bandit Learning in Matching Markets NIPS 2024
Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms NIPS 2024
Gaussian Process Bandits for Top-k Recommendations NIPS 2024
Context-Aware Assistant Selection for Improved Inference Acceleration with Large Language Models EMNLP 2024
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach AAAI 2024