regret bound

Dimension-Free Exponentiated Gradient NeurIPS 2013 Eluder Dimension and the Sample Complexity of Optimistic Exploration NeurIPS 2013 From Bandits to Experts: A Tale of Domination and Independence NeurIPS 2013 Further Optimal Regret Bounds for Thompson Sampling AISTATS 2013 Hierarchical Regularization Cascade for Joint Learning ICML 2013 High-Dimensional Gaussian Process Bandits NeurIPS 2013 Learning Prices for Repeated Auctions with Strategic Buyers NeurIPS 2013 Learning Trajectory Preferences for Manipulators via Iterative Improvement NeurIPS 2013 Localization and Adaptation in Online Learning AISTATS 2013 Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem JMLR 2013 Minimax Optimal Algorithms for Unconstrained Linear Optimization NeurIPS 2013 (More) Efficient Reinforcement Learning via Posterior Sampling NeurIPS 2013 Multi-armed Bandit Problem with Lock-up Periods ACML 2013 (Nearly) Optimal Algorithms for Private Online Learning in Full-information and Bandit Settings NeurIPS 2013 Online learning in episodic Markovian decision processes by relative entropy policy search NeurIPS 2013 Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions NeurIPS 2013 Online Learning of Dynamic Parameters in Social Networks NeurIPS 2013 Online Learning under Delayed Feedback ICML 2013 Online Learning with Costly Features and Labels NeurIPS 2013 Online Learning with Predictable Sequences COLT 2013 Online Learning with Switching Costs and Other Adaptive Adversaries NeurIPS 2013 On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization COLT 2013 On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation NeurIPS 2013 Open Problem: Adversarial Multiarmed Bandits with Limited Advice COLT 2013 Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality JMLR 2013