regret bound

-Armed Bandits JMLR 2011 A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011 Bandits, Query Learning, and the Haystack Dimension COLT 2011 Better Algorithms for Benign Bandits JMLR 2011 Committing Bandits NeurIPS 2011 Contextual Bandit Algorithms with Supervised Learning Guarantees AISTATS 2011 Contextual Bandits with Linear Payoff Functions AISTATS 2011 Contextual Gaussian Process Bandit Optimization NeurIPS 2011 Finite Time Analysis of Stratified Sampling for Monte Carlo NeurIPS 2011 From Bandits to Experts: On the Value of Side-Observations NeurIPS 2011 Greedy Model Averaging NeurIPS 2011 Improved Algorithms for Linear Stochastic Bandits NeurIPS 2011 Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback AISTATS 2011 Learning Eigenvectors for Free NeurIPS 2011 Linear Submodular Bandits and their Application to Diversified Retrieval NeurIPS 2011 Monotone multi-armed bandit allocations COLT 2011 Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction NeurIPS 2011 On the Universality of Online Mirror Descent NeurIPS 2011 PAC-Bayesian Analysis of Contextual Bandits NeurIPS 2011 Predicting Dynamic Difficulty NeurIPS 2011 Prediction strategies without loss NeurIPS 2011 Regret Bounds for the Adaptive Control of Linear Quadratic Systems COLT 2011 Selecting the State-Representation in Reinforcement Learning NeurIPS 2011 Sparsity Regret Bounds for Individual Sequences in Online Linear Regression COLT 2011 Stochastic convex optimization with bandit feedback NeurIPS 2011