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Multi-Armed Bandits

1044 directly classified papers

Papers per year

Papers

Adaptive Influence Maximization with Myopic Feedback NIPS 2019
A fully adaptive algorithm for pure exploration in linear bandits AISTATS 2018
Normal Bandits of Unknown Means and Variances JMLR 2018
Uncovering Causality from Multivariate Hawkes Integrated Cumulants JMLR 2018
Firing Bandits: Optimizing Crowdfunding ICML 2018
Bandit Learning with Positive Externalities NIPS 2018
Reward Maximization Under Uncertainty: Leveraging Side-Observations on Networks JMLR 2018
Contextual bandits with surrogate losses: Margin bounds and efficient algorithms NIPS 2018
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs NIPS 2018
Contextual Combinatorial Multi-armed Bandits with Volatile Arms and Submodular Reward NIPS 2018
Fighting Boredom in Recommender Systems with Linear Reinforcement Learning NIPS 2018
Factored Bandits NIPS 2018
Adaptation to Easy Data in Prediction with Limited Advice NIPS 2018
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem NIPS 2018
Coordinate Descent with Bandit Sampling NIPS 2018
Contextual Pricing for Lipschitz Buyers NIPS 2018
Regret Bounds for Online Portfolio Selection with a Cardinality Constraint NIPS 2018
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling NIPS 2018
A Bandit Approach to Sequential Experimental Design with False Discovery Control NIPS 2018
Adversarial Attacks on Stochastic Bandits NIPS 2018
Adaptive Learning with Unknown Information Flows NIPS 2018
Differentially Private Contextual Linear Bandits NIPS 2018
Efficient nonmyopic batch active search NIPS 2018
Structural Causal Bandits: Where to Intervene? NIPS 2018
Distributed Multi-Player Bandits - a Game of Thrones Approach NIPS 2018