online learning

Learning to Crawl AAAI 2020 Learning to Guide Random Search ICLR 2020 Learning to Learn with Feedback and Local Plasticity NeurIPS 2020 Learning to Play Sequential Games versus Unknown Opponents NeurIPS 2020 Learning URI Selection Criteria to Improve the Crawling of Linked Open Data (Extended Abstract) IJCAI 2020 Linear Bandits with Feature Feedback AAAI 2020 Lipschitz and Comparator-Norm Adaptivity in Online Learning COLT 2020 (Locally) Differentially Private Combinatorial Semi-Bandits ICML 2020 Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems NeurIPS 2020 Look-ahead Meta Learning for Continual Learning NeurIPS 2020 Manipulation Trajectory Optimization with Online Grasp Synthesis and Selection RSS 2020 Memoryless Sequences for General Losses JMLR 2020 Meta-Consolidation for Continual Learning NeurIPS 2020 Meta-Gradient Reinforcement Learning with an Objective Discovered Online NeurIPS 2020 Metric-Free Individual Fairness in Online Learning NeurIPS 2020 Minimizing Dynamic Regret and Adaptive Regret Simultaneously AISTATS 2020 Mixed Strategies for Robust Optimization of Unknown Objectives AISTATS 2020 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020 Model Selection in Contextual Stochastic Bandit Problems NeurIPS 2020 Naive Exploration is Optimal for Online LQR ICML 2020 Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs IJCAI 2020 Near-optimal Regret Bounds for Stochastic Shortest Path ICML 2020 New Potential-Based Bounds for Prediction with Expert Advice COLT 2020 Nonparametric Sequential Prediction While Deep Learning the Kernel AISTATS 2020 No-Regret and Incentive-Compatible Online Learning ICML 2020