Online Algorithms

Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games ICML 2020 First-Order Bayesian Regret Analysis of Thompson Sampling ALT 2020 First-Order Methods for Large-Scale Market Equilibrium Computation NeurIPS 2020 Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games NeurIPS 2020 Frequency Configuration for Low-Power Wide-Area Networks in a Heartbeat NSDI 2020 From Finite to Countable-Armed Bandits NeurIPS 2020 Gamification of Pure Exploration for Linear Bandits ICML 2020 Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits UAI 2020 Geometric Exploration for Online Control NeurIPS 2020 Gradient-free Online Learning in Continuous Games with Delayed Rewards ICML 2020 Group-Fair Online Allocation in Continuous Time NeurIPS 2020 Hedging in games: Faster convergence of external and swap regrets NeurIPS 2020 High-Dimensional Sparse Linear Bandits NeurIPS 2020 Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space IJCAI 2020 Hypothetical Answers to Continuous Queries over Data Streams AAAI 2020 ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool NeurIPS 2020 Improper Learning for Non-Stochastic Control COLT 2020 Improved Algorithms for Conservative Exploration in Bandits AAAI 2020 Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds NeurIPS 2020 Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020 Improving Online Rent-or-Buy Algorithms with Sequential Decision Making and ML Predictions NeurIPS 2020 Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020 Incremental Fairness in Two-Sided Market Platforms: On Smoothly Updating Recommendations AAAI 2020 Inference for Batched Bandits NeurIPS 2020 Latent Bandits Revisited NeurIPS 2020