contextual bandit

A Bayesian Approach for Subset Selection in Contextual Bandits AAAI 2021 A Contextual Bandit Bake-off JMLR 2021 Adapting to misspecification in contextual bandits with offline regression oracles ICML 2021 Adversarial Linear Contextual Bandits with Graph-Structured Side Observations AAAI 2021 An Efficient Algorithm for Deep Stochastic Contextual Bandits AAAI 2021 An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling AISTATS 2021 A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits AISTATS 2021 Bandits with Knapsacks beyond the Worst Case NeurIPS 2021 Bandits with partially observable confounded data UAI 2021 Bayesian decision-making under misspecified priors with applications to meta-learning NeurIPS 2021 Confidence-Budget Matching for Sequential Budgeted Learning ICML 2021 Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting AISTATS 2021 Contextual Bandits with Delayed Feedback and Semi-supervised Learning (Student Abstract) AAAI 2021 Contextual Blocking Bandits AISTATS 2021 Contextual Recommendations and Low-Regret Cutting-Plane Algorithms NeurIPS 2021 Control Variates for Slate Off-Policy Evaluation NeurIPS 2021 Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns AISTATS 2021 Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks NeurIPS 2021 Design of Experiments for Stochastic Contextual Linear Bandits NeurIPS 2021 Doubly Robust Thompson Sampling with Linear Payoffs NeurIPS 2021 Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination NeurIPS 2021 Fairness of Exposure in Stochastic Bandits ICML 2021 Federated Linear Contextual Bandits NeurIPS 2021 Generalized Linear Bandits with Local Differential Privacy NeurIPS 2021 Individual Fairness in Hindsight JMLR 2021