Multi-Armed Bandits

Fighting Boredom in Recommender Systems with Linear Reinforcement Learning NeurIPS 2018 Firing Bandits: Optimizing Crowdfunding ICML 2018 Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits ICML 2018 Minimax Concave Penalized Multi-Armed Bandit Model with High-Dimensional Covariates ICML 2018 Mitigating Bias in Adaptive Data Gathering via Differential Privacy ICML 2018 Multinomial Logit Bandit with Linear Utility Functions IJCAI 2018 Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models NeurIPS 2018 Nonstochastic Bandits with Composite Anonymous Feedback COLT 2018 Normal Bandits of Unknown Means and Variances JMLR 2018 Online Pricing for Revenue Maximization with Unknown Time Discounting Valuations IJCAI 2018 PG-TS: Improved Thompson Sampling for Logistic Contextual Bandits NeurIPS 2018 Policy Evaluation and Optimization with Continuous Treatments AISTATS 2018 Practical Contextual Bandits with Regression Oracles ICML 2018 Profitable Bandits ACML 2018 Refining the Confidence Level for Optimistic Bandit Strategies JMLR 2018 Regret Bounds for Online Portfolio Selection with a Cardinality Constraint NeurIPS 2018 Reward Maximization Under Uncertainty: Leveraging Side-Observations on Networks JMLR 2018 Semiparametric Contextual Bandits ICML 2018 Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling NeurIPS 2018 Structural Causal Bandits: Where to Intervene? NeurIPS 2018 UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits IJCAI 2018 Uncovering Causality from Multivariate Hawkes Integrated Cumulants JMLR 2018 Using Contextual Bandits with Behavioral Constraints for Constrained Online Movie Recommendation IJCAI 2018 Variational inference for the multi-armed contextual bandit AISTATS 2018 Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer ICML 2018