online mirror descent

Learning in two-player zero-sum partially observable Markov games with perfect recall NeurIPS 2021 Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition COLT 2021 Online Markov Decision Processes with Aggregate Bandit Feedback COLT 2021 Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits JMLR 2021 A Closer Look at Small-loss Bounds for Bandits with Graph Feedback COLT 2020 Dual Mirror Descent for Online Allocation Problems ICML 2020 No-regret Learning in Price Competitions under Consumer Reference Effects NeurIPS 2020 Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach ICLR 2020 Prediction with Corrupted Expert Advice NeurIPS 2020 Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses NeurIPS 2020 An Optimal Algorithm for Stochastic and Adversarial Bandits AISTATS 2019 Exponential Weights on the Hypercube in Polynomial Time AISTATS 2019 Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing JMLR 2019 Online-Within-Online Meta-Learning NeurIPS 2019 Efficient Online Portfolio with Logarithmic Regret NeurIPS 2018 More Adaptive Algorithms for Adversarial Bandits COLT 2018 Nearly second-order optimality of online joint detection and estimation via one-sample update schemes AISTATS 2018 Corralling a Band of Bandit Algorithms COLT 2017 Countering Feedback Delays in Multi-Agent Learning NeurIPS 2017 On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities COLT 2017 Online Decision-Making in General Combinatorial Spaces NeurIPS 2014 On the Universality of Online Mirror Descent NeurIPS 2011