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Multi-Armed Bandits

1044 directly classified papers

Papers per year

Papers

Learning the Learning Rate for Prediction with Expert Advice NIPS 2014
Efficient Partial Monitoring with Prior Information NIPS 2014
The Blinded Bandit: Learning with Adaptive Feedback NIPS 2014
Extreme bandits NIPS 2014
Almost Optimal Exploration in Multi-Armed Bandits ICML 2013
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal NIPS 2013
Information Complexity in Bandit Subset Selection COLT 2013
Beating Bandits in Gradually Evolving Worlds COLT 2013
Bounded regret in stochastic multi-armed bandits COLT 2013
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization COLT 2013
Opportunistic Strategies for Generalized No-Regret Problems COLT 2013
Multiple Identifications in Multi-Armed Bandits ICML 2013
Regret Minimization for Branching Experts COLT 2013
A near-optimal algorithm for finite partial-monitoring games against adversarial opponents COLT 2013
Adaptive Submodular Maximization in Bandit Setting NIPS 2013
(Nearly) Optimal Algorithms for Private Online Learning in Full-information and Bandit Settings NIPS 2013
Thompson Sampling for 1-Dimensional Exponential Family Bandits NIPS 2013
From Bandits to Experts: A Tale of Domination and Independence NIPS 2013
Online Learning with Switching Costs and Other Adaptive Adversaries NIPS 2013
High-Dimensional Gaussian Process Bandits NIPS 2013
Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising NIPS 2013
Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting NIPS 2013
Eluder Dimension and the Sample Complexity of Optimistic Exploration NIPS 2013
Prior-free and prior-dependent regret bounds for Thompson Sampling NIPS 2013
A Gang of Bandits NIPS 2013