upper confidence bound

Bayesian Optimization with Cost-varying Variable Subsets NeurIPS 2023 Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments NeurIPS 2023 Combinatorial Neural Bandits ICML 2023 Communication-Constrained Bandits under Additive Gaussian Noise ICML 2023 Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards NeurIPS 2023 Decentralized Stochastic Multi-Player Multi-Armed Walking Bandits AAAI 2023 Failure-Aware Gaussian Process Optimization with Regret Bounds NeurIPS 2023 Federated Neural Bandits ICLR 2023 Finite-Time Logarithmic Bayes Regret Upper Bounds NeurIPS 2023 Improved Online Learning Algorithms for CTR Prediction in Ad Auctions ICML 2023 Latent Variable Representation for Reinforcement Learning ICLR 2023 Learning to Rank under Multinomial Logit Choice JMLR 2023 Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB AISTATS 2023 Maximum Average Randomly Sampled: A Scale Free and Non-parametric Algorithm for Stochastic Bandits NeurIPS 2023 Monte Carlo Tree Search with Boltzmann Exploration NeurIPS 2023 Multi-Agent Learning with Heterogeneous Linear Contextual Bandits NeurIPS 2023 Non-Asymptotic Analysis of a UCB-based Top Two Algorithm NeurIPS 2023 On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits ICML 2023 On the Sublinear Regret of GP-UCB NeurIPS 2023 Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework NeurIPS 2023 Optimistic Whittle Index Policy: Online Learning for Restless Bandits AAAI 2023 Provably Efficient Lifelong Reinforcement Learning with Linear Representation ICLR 2023 Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds ICML 2023 Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents ICML 2023 Risk-aware linear bandits with convex loss AISTATS 2023