regret minimization

Random Effect Bandits AISTATS 2022 Rate-Optimal Online Convex Optimization in Adaptive Linear Control NeurIPS 2022 Regret Minimization with Performative Feedback ICML 2022 Regret, stability & fairness in matching markets with bandit learners AISTATS 2022 Reinforcement Learning with Logarithmic Regret and Policy Switches NeurIPS 2022 Safe Control with Minimal Regret L4DC 2022 Safe Subgame Resolving for Extensive Form Correlated Equilibrium AAAI 2022 Search-based Reinforcement Learning through Bandit Linear Optimization IJCAI 2022 Sequential Information Design: Learning to Persuade in the Dark NeurIPS 2022 Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models ICML 2022 Strategizing against Learners in Bayesian Games COLT 2022 Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning ACML 2022 Versatile Dueling Bandits: Best-of-both World Analyses for Learning from Relative Preferences ICML 2022 Achieving Fairness in the Stochastic Multi-Armed Bandit Problem JMLR 2021 Adversarial Dueling Bandits ICML 2021 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits ICML 2021 A Regret Minimization Approach to Iterative Learning Control ICML 2021 Bandit algorithms: Letting go of logarithmic regret for statistical robustness AISTATS 2021 Beyond $log^2(T)$ regret for decentralized bandits in matching markets ICML 2021 Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving NeurIPS 2021 Decentralized Learning in Online Queuing Systems NeurIPS 2021 Deciding What to Learn: A Rate-Distortion Approach ICML 2021 Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games ICML 2021 Experimental Design for Regret Minimization in Linear Bandits AISTATS 2021 Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games AAAI 2021