conftrace_

regret bound

1926 papers

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RB

Co-occurring keywords

online learning (1777) multi-armed bandit (1098) contextual bandit (381) stochastic optimization (1060) reinforcement learning (4352) online algorithm (445) upper confidence bound (197) markov decision process (790) thompson sampling (237) online convex optimization (165)

Papers

Logarithmic Regret for Episodic Continuous-Time Linear-Quadratic Reinforcement Learning over a Finite-Time Horizon JMLR 2022
Feature and Parameter Selection in Stochastic Linear Bandits ICML 2022
Stochastic Rising Bandits ICML 2022
Nested Bandits ICML 2022
Multi-slots Online Matching with High Entropy ICML 2022
Safe Online Convex Optimization with Unknown Linear Safety Constraints AAAI 2022
Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits ICML 2022
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback ICML 2022
Procrastinated Tree Search: Black-Box Optimization with Delayed, Noisy, and Multi-Fidelity Feedback AAAI 2022
An Information-Theoretic Framework for Deep Learning NIPS 2022
Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space NIPS 2022
A Simple Unified Framework for High Dimensional Bandit Problems ICML 2022
ActiveHedge: Hedge meets Active Learning ICML 2022
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback ICML 2022
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits ICML 2022
A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds ICML 2022
No-Regret Learning in Partially-Informed Auctions ICML 2022
UniRank: Unimodal Bandit Algorithms for Online Ranking ICML 2022
Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games ICML 2022
Shuffle Private Linear Contextual Bandits ICML 2022
Game Redesign in No-regret Game Playing IJCAI 2022
Complete Policy Regret Bounds for Tallying Bandits COLT 2022
Open Problem: Regret Bounds for Noise-Free Kernel-Based Bandits COLT 2022
Thompson Sampling Achieves $\tilde{O}(\sqrt{T})$ Regret in Linear Quadratic Control COLT 2022
Towards Optimal Algorithms for Multi-Player Bandits without Collision Sensing Information COLT 2022