conftrace_

online mirror descent

40 papers

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Also known as

OMD

Co-occurring keywords

regret bound (1926) online learning (1777) multi-armed bandit (1098) nash equilibrium (398) extensive-form game (86) online convex optimization (165) game theory (854) stochastic optimization (1060) adversarial bandit (59) mirror descent (148)

Papers

Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization JMLR 2024
Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror Descent IJCAI 2024
Local and Adaptive Mirror Descents in Extensive-Form Games NIPS 2024
Learning $\epsilon$-Nash equilibrium stationary policies in stochastic games with unknown independent chains using online mirror descent L4DC 2024
On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games NIPS 2024
Extensive-Form Game Solving via Blackwell Approachability on Treeplexes NIPS 2024
No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling NIPS 2023
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization ICML 2023
Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning ICML 2023
Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs ALT 2023
Learning Sparse Graphon Mean Field Games AISTATS 2023
Meta-Learning Adversarial Bandit Algorithms NIPS 2023
Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case JMLR 2022
Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent ICML 2022
Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information L4DC 2022
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent NIPS 2022
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games ICML 2022
Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback NIPS 2022
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits JMLR 2021
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition COLT 2021
Learning in two-player zero-sum partially observable Markov games with perfect recall NIPS 2021
Online Markov Decision Processes with Aggregate Bandit Feedback COLT 2021
Faster Game Solving via Predictive Blackwell Approachability: Connecting Regret Matching and Mirror Descent AAAI 2021
Prediction with Corrupted Expert Advice NIPS 2020
No-regret Learning in Price Competitions under Consumer Reference Effects NIPS 2020