Hongtu Zhu

发表

A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets

C. Shi, R. Song, Runzhe Wan, 2022, ArXiv.

Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching

Jieping Ye, Zhiwei Qin, Xiaocheng Tang, 2021, 2021 IEEE International Conference on Data Mining (ICDM).

Reinforcement Learning for Ridesharing: An Extended Survey

Jieping Ye, Zhiwei Qin, Hongtu Zhu, 2021, 2105.01099.

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons

C. Shi, R. Song, S. Luo, 2022, Journal of the American Statistical Association.

A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets

C. Shi, R. Song, Runzhe Wan, 2022, ArXiv.

Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms

Jieping Ye, C. Shi, S. Luo, 2022, ArXiv.

Optimizing Bike-Share Repositioning: Networked Inventory Management with Spatiotemporal Modeling

Zhiwei Qin, Hongtu Zhu, Chunyi Liu, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework

Jieping Ye, C. Shi, R. Song, 2020, Journal of the American Statistical Association.

Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms

Yongxin Tong, Jieping Ye, Xiaocheng Tang, 2021, KDD.

Graph-Based Equilibrium Metrics for Dynamic Supply–Demand Systems With Applications to Ride-sourcing Platforms

Jieping Ye, S. Luo, Hongtu Zhu, 2021, Journal of the American Statistical Association.

Reinforcement learning for ridesharing: An extended survey

Jieping Ye, Zhiwei Qin, Hongtu Zhu, 2021, Transportation Research Part C: Emerging Technologies.

Reinforcement Learning for Ridesharing: A Survey

Jieping Ye, Zhiwei Qin, Hongtu Zhu, 2021, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC).

Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching

Jieping Ye, Hongtu Zhu, Zhiwei Qin, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

Origin-destination Flow Prediction with Vehicle Trajectory Data and Semi-supervised Recurrent Neural Network

Jianfeng Zheng, Tao Huang, Henry X. Liu, 2019, 2019 IEEE International Conference on Big Data (Big Data).

A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Zhe Xu, Jieping Ye, Hongtu Zhu, 2019, KDD.

Optimal passenger-seeking policies on E-hailing platforms using Markov decision process and imitation learning

Jieping Ye, Xuan Di, R. Hampshire, 2019, Transportation Research Part C: Emerging Technologies.

KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces

Zhiwei Qin, M. Korayem, Liangjie Hong, 2022, SIGKDD Explor..

Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond

Zhiwei Qin, M. Korayem, Liangjie Hong, 2022, KDD.

Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning pdf

Fan Zhang, Jieping Ye, Xiaocheng Tang, 2021, ArXiv.

Ride-Hailing Order Dispatching at DiDi via Reinforcement Learning

Fan Zhang, Jieping Ye, Zhe Xu, 2020, INFORMS J. Appl. Anal..

A Reinforcement Learning Framework for Time-Dependent Causal Effects Evaluation in A/B Testing

Jieping Ye, C. Shi, R. Song, 2020, ArXiv.

A generalized fluid model of ride-hailing systems

X. Chao, Jieping Ye, Yafeng Yin, 2021, Transportation Research Part B: Methodological.

Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing

C. Shi, Zhaohua Lu, Ting Li, 2023, Journal of the American Statistical Association.

A Multi-Agent Reinforcement Learning Framework for Off-Policy Evaluation in Two-sided Markets

C. Shi, R. Song, Runzhe Wan, 2022, The Annals of Applied Statistics.

Reinforcement learning for ridesharing: An extended survey

Jieping Ye, Zhiwei Qin, Hongtu Zhu, 2021, Transportation Research Part C: Emerging Technologies.

Adversarial Learning of Distributional Reinforcement Learning

Fan Zhou, Yukun Huang, Hongtu Zhu, 2023, ICML.

A Deep Value-based Policy Search Approach for Real-world Vehicle Repositioning on Mobility-on-Demand Platforms

Jieping Ye, Zhiwei Qin, Xiaocheng Tang, 2020 .

InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms

Bo An, Jieping Ye, Hongtu Zhu, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

A Joint Inverse Reinforcement Learning and Deep Learning Model for Drivers' Behavioral Prediction

Qichao Wang, Jing He, Jieping Ye, 2020, CIKM.

CGT: Clustered Graph Transformer for Urban Spatio-temporal Prediction

Qiang Yang, Jieping Ye, Leye Wang, 2019 .

Development of a one-day driving cycle for electric ride-hailing vehicles

Hai Yang, Xiaoran Qin, Jieping Ye, 2020 .

Multi-party ride-matching problem in the ride-hailing market with bundled option services

Hongtu Zhu, Hai Yang, Yinghui Wu, 2021 .

Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms

Jieping Ye, C. Shi, S. Luo, 2022, ArXiv.