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Multi-Armed Bandits

1,057 papers

Papers per year

5
27
87
38
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Papers

Revenue Optimization against Strategic Buyers NIPS 2015
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions NIPS 2015
Fighting Bandits with a New Kind of Smoothness NIPS 2015
Convergence Analysis of Prediction Markets via Randomized Subspace Descent NIPS 2015
The Pareto Regret Frontier for Bandits NIPS 2015
Bandits with Unobserved Confounders: A Causal Approach NIPS 2015
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach NIPS 2015
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation NIPS 2015
Linear Multi-Resource Allocation with Semi-Bandit Feedback NIPS 2015
Online Learning with Gaussian Payoffs and Side Observations NIPS 2015
Copeland Dueling Bandits NIPS 2015
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs NIPS 2015
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring NIPS 2015
Explore no more: Improved high-probability regret bounds for non-stochastic bandits NIPS 2015
Budgeted Bandit Problems with Continuous Random Costs ACML 2015
Bandit Convex Optimization: \sqrtT Regret in One Dimension COLT 2015
Contextual Dueling Bandits COLT 2015
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem COLT 2015
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback ICML 2015
Efficient Learning in Large-Scale Combinatorial Semi-Bandits ICML 2015
Simple regret for infinitely many armed bandits ICML 2015
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays ICML 2015
On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments ICML 2015
Qualitative Multi-Armed Bandits: A Quantile-Based Approach ICML 2015
Cheap Bandits ICML 2015