Online Algorithms

Robust Multi-objective Learning with Mentor Feedback COLT 2014 Set-Valued Approachability and Online Learning with Partial Monitoring JMLR 2014 Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits ICML 2014 The Blinded Bandit: Learning with Adaptive Feedback NeurIPS 2014 Three Guidelines of Online Learning for Large-Scale Visual Recognition CVPR 2014 Towards Minimax Online Learning with Unknown Time Horizon ICML 2014 Adaptive Market Making via Online Learning NeurIPS 2013 Adaptive Submodular Maximization in Bandit Setting NeurIPS 2013 Almost Optimal Exploration in Multi-Armed Bandits ICML 2013 A near-optimal algorithm for finite partial-monitoring games against adversarial opponents COLT 2013 Approachability, fast and slow COLT 2013 A Tale of Two Metrics: Simultaneous Bounds on Competitiveness and Regret COLT 2013 Beating Bandits in Gradually Evolving Worlds COLT 2013 Bounded regret in stochastic multi-armed bandits COLT 2013 Combinatorial Multi-Armed Bandit: General Framework and Applications ICML 2013 Competing with an Infinite Set of Models in Reinforcement Learning AISTATS 2013 Competing With Strategies COLT 2013 Dimension-Free Exponentiated Gradient NeurIPS 2013 Distributed Exploration in Multi-Armed Bandits NeurIPS 2013 Dynamical Models and tracking regret in online convex programming ICML 2013 From Bandits to Experts: A Tale of Domination and Independence NeurIPS 2013 How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal NeurIPS 2013 Large-Scale Learning with Less RAM via Randomization ICML 2013 Minimax Optimal Algorithms for Unconstrained Linear Optimization NeurIPS 2013 One-Pass AUC Optimization ICML 2013