regret bound

Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication ICLR 2020 Distributed Primal-Dual Optimization for Online Multi-Task Learning AAAI 2020 Dual Mirror Descent for Online Allocation Problems ICML 2020 Dynamic Assortment Optimization with Changing Contextual Information JMLR 2020 Efficient and robust algorithms for adversarial linear contextual bandits COLT 2020 Efficient and Robust High-Dimensional Linear Contextual Bandits IJCAI 2020 Efficient improper learning for online logistic regression COLT 2020 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation ICML 2020 Efficient Projection-Free Online Methods with Stochastic Recursive Gradient AAAI 2020 Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NeurIPS 2020 Exploiting the Surrogate Gap in Online Multiclass Classification NeurIPS 2020 Exploration Analysis in Finite-Horizon Turn-based Stochastic Games UAI 2020 Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits ICML 2020 Extreme Tensoring for Low-Memory Preconditioning ICLR 2020 Faster Projection-free Online Learning COLT 2020 Fast Rates for Online Prediction with Abstention COLT 2020 Fatigue-Aware Bandits for Dependent Click Models AAAI 2020 Feedback graph regret bounds for Thompson Sampling and UCB ALT 2020 Finite Continuum-Armed Bandits NeurIPS 2020 Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent COLT 2020 Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NeurIPS 2020 Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games NeurIPS 2020 Frequentist Regret Bounds for Randomized Least-Squares Value Iteration AISTATS 2020 From Finite to Countable-Armed Bandits NeurIPS 2020 From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model ICML 2020