Online Algorithms

Linear Bandits with Feature Feedback AAAI 2020 Lipschitz and Comparator-Norm Adaptivity in Online Learning COLT 2020 Logarithmic Regret for Adversarial Online Control ICML 2020 Memoryless Sequences for General Losses JMLR 2020 Minimizing Dynamic Regret and Adaptive Regret Simultaneously AISTATS 2020 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020 Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds AAAI 2020 Neural Contextual Bandits with UCB-based Exploration ICML 2020 Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without COLT 2020 No-Regret and Incentive-Compatible Online Learning ICML 2020 No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix NeurIPS 2020 No-Regret Prediction in Marginally Stable Systems COLT 2020 Old Dog Learns New Tricks: Randomized UCB for Bandit Problems AISTATS 2020 OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting AAAI 2020 Online Agnostic Boosting via Regret Minimization NeurIPS 2020 Online Bayesian Persuasion NeurIPS 2020 Online Convex Optimization with Perturbed Constraints: Optimal Rates against Stronger Benchmarks AISTATS 2020 Online Decision Based Visual Tracking via Reinforcement Learning NeurIPS 2020 Online Learning Using Only Peer Prediction AISTATS 2020 Online Learning with Continuous Variations: Dynamic Regret and Reductions AISTATS 2020 Online Learning with Dependent Stochastic Feedback Graphs ICML 2020 Online Learning with Imperfect Hints ICML 2020 Online Learning with Primary and Secondary Losses NeurIPS 2020 Online Learning with Vector Costs and Bandits with Knapsacks COLT 2020 Online Linear Optimization with Many Hints NeurIPS 2020