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

Surrogate Regret Bounds for the Area Under the ROC Curve via Strongly Proper Losses COLT 2013
Beating Bandits in Gradually Evolving Worlds COLT 2013
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization COLT 2013
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions NIPS 2013
(Nearly) Optimal Algorithms for Private Online Learning in Full-information and Bandit Settings NIPS 2013
Adaptive Submodular Maximization in Bandit Setting NIPS 2013
Localization and Adaptation in Online Learning AISTATS 2013
A Last-Step Regression Algorithm for Non-Stationary Online Learning AISTATS 2013
Combinatorial Multi-Armed Bandit: General Framework and Applications ICML 2013
Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem JMLR 2013
The Pareto Regret Frontier NIPS 2013
Online Learning of Dynamic Parameters in Social Networks NIPS 2013
Prior-free and prior-dependent regret bounds for Thompson Sampling NIPS 2013
Aggregating Optimistic Planning Trees for Solving Markov Decision Processes NIPS 2013
Adaptive Market Making via Online Learning NIPS 2013
An Active Learning Algorithm for Ranking from Pairwise Preferences with an Almost Optimal Query Complexity JMLR 2012
Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems NIPS 2012
Imitation Learning by Coaching NIPS 2012
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning NIPS 2012
Risk-Aversion in Multi-armed Bandits NIPS 2012
No-Regret Algorithms for Unconstrained Online Convex Optimization NIPS 2012
Distributed Non-Stochastic Experts NIPS 2012
Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits AISTATS 2012
Open Problem: Better Bounds for Online Logistic Regression COLT 2012
The Best of Both Worlds: Stochastic and Adversarial Bandits COLT 2012