Multi-Armed Bandits

Anytime optimal algorithms in stochastic multi-armed bandits ICML 2016 BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits ICML 2016 Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design ICML 2016 Causal Bandits: Learning Good Interventions via Causal Inference NeurIPS 2016 Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms JMLR 2016 Conservative Bandits ICML 2016 Contextual Combinatorial Cascading Bandits ICML 2016 Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm ICML 2016 DCM Bandits: Learning to Rank with Multiple Clicks ICML 2016 Distributed Clustering of Linear Bandits in Peer to Peer Networks ICML 2016 Double Thompson Sampling for Dueling Bandits NeurIPS 2016 Efficient Algorithms for Adversarial Contextual Learning ICML 2016 Importance Weighting Without Importance Weights: An Efficient Algorithm for Combinatorial Semi-Bandits JMLR 2016 Improved Learning Complexity in Combinatorial Pure Exploration Bandits AISTATS 2016 Learning Algorithms for Second-Price Auctions with Reserve JMLR 2016 Machine Learning in an Auction Environment JMLR 2016 Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution NeurIPS 2016 Multi-armed Bandits: Competing with Optimal Sequences NeurIPS 2016 Multiple-Play Bandits in the Position-Based Model NeurIPS 2016 No-Regret Algorithms for Heavy-Tailed Linear Bandits ICML 2016 Online Pricing with Strategic and Patient Buyers NeurIPS 2016 Online Stochastic Linear Optimization under One-bit Feedback ICML 2016 Optimistic Bandit Convex Optimization NeurIPS 2016 Optimistic Gittins Indices NeurIPS 2016 Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games NeurIPS 2016