contextual bandit

Context-Aware Assistant Selection for Improved Inference Acceleration with Large Language Models EMNLP 2024 Contextual Bandits with Budgeted Information Reveal AISTATS 2024 Contextual Bandits with Online Neural Regression ICLR 2024 Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression JMLR 2024 Contextual Multinomial Logit Bandits with General Value Functions NeurIPS 2024 Contextual Pandora’s Box AAAI 2024 Efficient Contextual Bandits with Uninformed Feedback Graphs ICML 2024 Efficient Interactive Maximization of BP and Weakly Submodular Objectives UAI 2024 Expert with clustering: Hierarchical online preference learning framework L4DC 2024 Fairness and Privacy Guarantees in Federated Contextual Bandits ACML 2024 Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits ICML 2024 Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users AAAI 2024 Federated Linear Contextual Bandits with Heterogeneous Clients AISTATS 2024 Gaussian Process Bandits for Top-k Recommendations NeurIPS 2024 Generalized Linear Bandits with Limited Adaptivity NeurIPS 2024 How Does Variance Shape the Regret in Contextual Bandits? NeurIPS 2024 Importance-Weighted Offline Learning Done Right ALT 2024 Improved Algorithms for Contextual Dynamic Pricing NeurIPS 2024 Is O(log N) practical? Near-Equivalence Between Delay Robustness and Bounded Regret in Bandits and RL NeurIPS 2024 Jump Starting Bandits with LLM-Generated Prior Knowledge EMNLP 2024 Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances ICLR 2024 Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit NeurIPS 2024 Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning NeurIPS 2024 Meta Learning in Bandits within shared affine Subspaces AISTATS 2024 Mixed-Effects Contextual Bandits AAAI 2024