conftrace_

regret bound

1926 papers

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Also known as

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

Adaptive Regret of Convex and Smooth Functions ICML 2019
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously ICML 2019
Bilinear Bandits with Low-rank Structure ICML 2019
POLITEX: Regret Bounds for Policy Iteration using Expert Prediction ICML 2019
Exploiting structure of uncertainty for efficient matroid semi-bandits ICML 2019
Learning to Collaborate in Markov Decision Processes ICML 2019
Online Convex Optimization in Adversarial Markov Decision Processes ICML 2019
CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration ICML 2019
AdaLinUCB: Opportunistic Learning for Contextual Bandits IJCAI 2019
A Practical Semi-Parametric Contextual Bandit IJCAI 2019
Incorporating Behavioral Constraints in Online AI Systems AAAI 2019
Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue AAAI 2019
Balanced Linear Contextual Bandits AAAI 2019
Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games AAAI 2019
Flattening a Hierarchical Clustering through Active Learning NIPS 2019
Bayesian Optimization under Heavy-tailed Payoffs NIPS 2019
Dying Experts: Efficient Algorithms with Optimal Regret Bounds NIPS 2019
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems NIPS 2019
Model Selection for Contextual Bandits NIPS 2019
Contextual Bandits with Cross-Learning NIPS 2019
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits NIPS 2019
Logarithmic Regret for Online Control NIPS 2019
Thompson Sampling and Approximate Inference NIPS 2019
Adaptive Gradient-Based Meta-Learning Methods NIPS 2019
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies NIPS 2019