regret bound

Efficient Adaptive Online Learning via Frequent Directions IJCAI 2018 Efficient Bandit Combinatorial Optimization Algorithm with Zero-suppressed Binary Decision Diagrams AISTATS 2018 Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning ICML 2018 Efficient Contextual Bandits in Non-stationary Worlds COLT 2018 Efficient online algorithms for fast-rate regret bounds under sparsity NeurIPS 2018 Efficient Online Portfolio with Logarithmic Regret NeurIPS 2018 Exploiting Strategy-Space Diversity for Batch Bayesian Optimization AISTATS 2018 Exploration in Structured Reinforcement Learning NeurIPS 2018 Factored Bandits NeurIPS 2018 Feasible Arm Identification ICML 2018 Fighting Boredom in Recommender Systems with Linear Reinforcement Learning NeurIPS 2018 Horizon-Independent Minimax Linear Regression NeurIPS 2018 Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems ICML 2018 Information Directed Sampling and Bandits with Heteroscedastic Noise COLT 2018 Instrument-Armed Bandits ALT 2018 Is Q-Learning Provably Efficient? NeurIPS 2018 Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems ICML 2018 Logistic Regression: The Importance of Being Improper COLT 2018 Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits ICML 2018 More Adaptive Algorithms for Adversarial Bandits COLT 2018 Multi-armed Bandits with Compensation NeurIPS 2018 Multi-Fidelity Black-Box Optimization with Hierarchical Partitions ICML 2018 Multinomial Logit Bandit with Linear Utility Functions IJCAI 2018 {Multi-Player Bandits Revisited} ALT 2018 Multiplicative Weights Updates with Constant Step-Size in Graphical Constant-Sum Games NeurIPS 2018