online learning

Optimistic Bayesian Sampling in Contextual-Bandit Problems JMLR 2012 Putting Bayes to sleep NeurIPS 2012 Real-Time Inverse Dynamics Learning for Musculoskeletal Robots based on Echo State Gaussian Process Regression RSS 2012 Relax and Randomize : From Value to Algorithms NeurIPS 2012 Security Analysis of Online Centroid Anomaly Detection JMLR 2012 Selective Sampling and Active Learning from Single and Multiple Teachers JMLR 2012 The adversarial stochastic shortest path problem with unknown transition probabilities AISTATS 2012 Transferring Expectations in Model-based Reinforcement Learning NeurIPS 2012 Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes NeurIPS 2012 Truncation-free Online Variational Inference for Bayesian Nonparametric Models NeurIPS 2012 Unified Algorithms for Online Learning and Competitive Analysis COLT 2012 Adaptive Hedge NeurIPS 2011 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization JMLR 2011 Agnostic KWIK learning and efficient approximate reinforcement learning COLT 2011 An Empirical Evaluation of Thompson Sampling NeurIPS 2011 A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning AISTATS 2011 A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011 Better Algorithms for Benign Bandits JMLR 2011 Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011 Committing Bandits NeurIPS 2011 Complexity-Based Approach to Calibration with Checking Rules COLT 2011 Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection AISTATS 2011 Contextual Bandit Algorithms with Supervised Learning Guarantees AISTATS 2011 Contextual Bandits with Linear Payoff Functions AISTATS 2011 Does an Efficient Calibrated Forecasting Strategy Exist? COLT 2011