Multi-Armed Bandits

Machine Teaching of Active Sequential Learners NeurIPS 2019 Making the Cut: A Bandit-based Approach to Tiered Interviewing NeurIPS 2019 MaxGap Bandit: Adaptive Algorithms for Approximate Ranking NeurIPS 2019 Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling AAAI 2019 Model Selection for Contextual Bandits NeurIPS 2019 Multi-Objective Generalized Linear Bandits IJCAI 2019 Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits COLT 2019 Non-Asymptotic Pure Exploration by Solving Games NeurIPS 2019 Nonparametric Contextual Bandits in Metric Spaces with Unknown Metric NeurIPS 2019 Nonstochastic Multiarmed Bandits with Unrestricted Delays NeurIPS 2019 Offline Contextual Bandits with High Probability Fairness Guarantees NeurIPS 2019 Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy ICLR 2019 On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits UAI 2019 Online EXP3 Learning in Adversarial Bandits with Delayed Feedback NeurIPS 2019 Online Learning via the Differential Privacy Lens NeurIPS 2019 Online Pandora’s Boxes and Bandits AAAI 2019 Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function NeurIPS 2019 On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons NeurIPS 2019 On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems NeurIPS 2019 Open Problem: Risk of Ruin in Multiarmed Bandits COLT 2019 Optimal Best Markovian Arm Identification with Fixed Confidence NeurIPS 2019 Optimal Testing in the Experiment-rich Regime AISTATS 2019 Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback NeurIPS 2019 Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach AAAI 2019 Personalizing Many Decisions with High-Dimensional Covariates NeurIPS 2019