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Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching., , , , , , and . ICDM, page 1541-1546. IEEE, (2021)Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation., , , and . WWW, page 292-302. ACM / IW3C2, (2020)Origin-destination Flow Prediction with Vehicle Trajectory Data and Semi-supervised Recurrent Neural Network., , , , , , and . IEEE BigData, page 1450-1459. IEEE, (2019)Deep Reinforcement Learning for Ride-sharing Dispatching and Repositioning., , , , , and . IJCAI, page 6566-6568. ijcai.org, (2019)Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching., , , , and . ICDM, page 617-626. IEEE Computer Society, (2018)A Deep Value-network Based Approach for Multi-Driver Order Dispatching., , , , , , , and . CoRR, (2021)Robust Low-Rank Tensor Recovery: Models and Algorithms., and . SIAM J. Matrix Anal. Appl., 35 (1): 225-253 (2014)InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms., , , , , , , and . ICDM, page 61-70. IEEE, (2019)Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation., , , , , and . KDD, page 566-576. ACM, (2019)Deep Reinforcement Learning with Applications in Transportation., , and . KDD, page 3201-3202. ACM, (2019)