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Multi-Armed Bandits

1,057 papers

Papers per year

5
27
87
38
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Papers

Optimistic Bandit Convex Optimization NIPS 2016
Causal Bandits: Learning Good Interventions via Causal Inference NIPS 2016
Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games NIPS 2016
Improved Learning Complexity in Combinatorial Pure Exploration Bandits AISTATS 2016
Online Stochastic Linear Optimization under One-bit Feedback ICML 2016
Anytime Exploration for Multi-armed Bandits using Confidence Information ICML 2016
DCM Bandits: Learning to Rank with Multiple Clicks ICML 2016
Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm ICML 2016
Contextual Combinatorial Cascading Bandits ICML 2016
Conservative Bandits ICML 2016
Distributed Clustering of Linear Bandits in Peer to Peer Networks ICML 2016
Anytime optimal algorithms in stochastic multi-armed bandits ICML 2016
Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design ICML 2016
No-Regret Algorithms for Heavy-Tailed Linear Bandits ICML 2016
BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits ICML 2016
Efficient Algorithms for Adversarial Contextual Learning ICML 2016
Scalable Discrete Sampling as a Multi-Armed Bandit Problem ICML 2016
Pricing a Low-regret Seller ICML 2016
Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms JMLR 2016
An Information-Theoretic Analysis of Thompson Sampling JMLR 2016
Learning Algorithms for Second-Price Auctions with Reserve JMLR 2016
Importance Weighting Without Importance Weights: An Efficient Algorithm for Combinatorial Semi-Bandits JMLR 2016
Machine Learning in an Auction Environment JMLR 2016
Combinatorial Bandits Revisited NIPS 2015
Combinatorial Cascading Bandits NIPS 2015