Online Algorithms

Online Learning with Sleeping Experts and Feedback Graphs ICML 2019 Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms NeurIPS 2019 Online Meta-Learning ICML 2019 Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis NeurIPS 2019 Online Pandora’s Boxes and Bandits AAAI 2019 Online Prediction of Switching Graph Labelings with Cluster Specialists NeurIPS 2019 Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function NeurIPS 2019 On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons NeurIPS 2019 On the Computational Power of Online Gradient Descent COLT 2019 On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems NeurIPS 2019 On the optimality of the Hedge algorithm in the stochastic regime JMLR 2019 On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation AAAI 2019 Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards ICML 2019 Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer NeurIPS 2019 Optimal Testing in the Experiment-rich Regime AISTATS 2019 Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions NeurIPS 2019 Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface AAAI 2019 Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback NeurIPS 2019 PAC Battling Bandits in the Plackett-Luce Model ALT 2019 PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits ICML 2019 Pareto Optimal Streaming Unsupervised Classification ICML 2019 Perturbed-History Exploration in Stochastic Linear Bandits UAI 2019 Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints NeurIPS 2019 Polynomial Cost of Adaptation for X-Armed Bandits NeurIPS 2019 Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach AAAI 2019