Online Algorithms

Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit AISTATS 2012 Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence NeurIPS 2012 Beyond Logarithmic Bounds in Online Learning AISTATS 2012 Confusion-Based Online Learning and a Passive-Aggressive Scheme NeurIPS 2012 Distributed Non-Stochastic Experts NeurIPS 2012 Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems NeurIPS 2012 Imitation Learning by Coaching NeurIPS 2012 Interpreting prediction markets: a stochastic approach NeurIPS 2012 Mirror Descent Meets Fixed Share (and feels no regret) NeurIPS 2012 Near-Optimal Algorithms for Online Matrix Prediction COLT 2012 No-Regret Algorithms for Unconstrained Online Convex Optimization NeurIPS 2012 Online allocation and homogeneous partitioning for piecewise constant mean-approximation NeurIPS 2012 Online L1-Dictionary Learning with Application to Novel Document Detection NeurIPS 2012 Online Optimization with Gradual Variations COLT 2012 Online Regret Bounds for Undiscounted Continuous Reinforcement Learning NeurIPS 2012 Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits AISTATS 2012 On Multilabel Classification and Ranking with Partial Feedback NeurIPS 2012 Open Problem: Better Bounds for Online Logistic Regression COLT 2012 Relax and Randomize : From Value to Algorithms NeurIPS 2012 Risk-Aversion in Multi-armed Bandits NeurIPS 2012 SpeedBoost: Anytime Prediction with Uniform Near-Optimality AISTATS 2012 The Best of Both Worlds: Stochastic and Adversarial Bandits COLT 2012 Towards Minimax Policies for Online Linear Optimization with Bandit Feedback COLT 2012 Unified Algorithms for Online Learning and Competitive Analysis COLT 2012 Adaptive Hedge NeurIPS 2011