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Exploration-Exploitation

155 papers

Papers per year

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Papers

The Pareto Regret Frontier for Bandits NIPS 2015
Linear Multi-Resource Allocation with Semi-Bandit Feedback NIPS 2015
Online Learning with Gaussian Payoffs and Side Observations NIPS 2015
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs NIPS 2015
Explore no more: Improved high-probability regret bounds for non-stochastic bandits NIPS 2015
The Blinded Bandit: Learning with Adaptive Feedback NIPS 2014
Repeated Contextual Auctions with Strategic Buyers NIPS 2014
Bayes-Adaptive Simulation-based Search with Value Function Approximation NIPS 2014
Optimal Neural Codes for Control and Estimation NIPS 2014
Learning to Optimize via Information-Directed Sampling NIPS 2014
Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards NIPS 2014
Discovering, Learning and Exploiting Relevance NIPS 2014
Best-Arm Identification in Linear Bandits NIPS 2014
A Gang of Bandits NIPS 2013
Prior-free and prior-dependent regret bounds for Thompson Sampling NIPS 2013
(More) Efficient Reinforcement Learning via Posterior Sampling NIPS 2013
Cost-Sensitive Exploration in Bayesian Reinforcement Learning NIPS 2012
Hierarchical Optimistic Region Selection driven by Curiosity NIPS 2012
Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence NIPS 2012
Analysis of Thompson Sampling for the Multi-armed Bandit Problem COLT 2012
Budgeted Optimization with Concurrent Stochastic-Duration Experiments NIPS 2011
Predicting Dynamic Difficulty NIPS 2011
Contextual Gaussian Process Bandit Optimization NIPS 2011
Random Walk Approach to Regret Minimization NIPS 2010
Learning from Logged Implicit Exploration Data NIPS 2010