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ORCIDZhiwei (Tony) Qin
Person information
- affiliation: DiDi Research America, Mountain View, Lyft Rideshare Labs, CA, USA
- affiliation: Walmart Labs, San Bruno, CA, USA
- affiliation (PhD 2013): Columbia University, New York, USA
Other persons with the same name
- Zhiwei Qin — disambiguation page
- Zhiwei Qin 0002
![[0000-0002-7387-5110]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-7387-5110")
— Chang'an University, College of Geological Engineering and Geomatics, Xi'an, China (and 1 more) - Zhiwei Qin 0003 — Harbin Institute of Technology, State Key Laboratory of Robotics and System, China
- Zhiwei Qin 0004 — Hong Kong Polytechnic University, Embedded Systems and CPS Laboratory, Department of Computing, Hung Hom, Kowloon, Hong Kong
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2020 – today
- 2024
[j11]Honghao Wei, Zixian Yang, Xin Liu, Zhiwei (Tony) Qin, Xiaocheng Tang, Lei Ying:
A Reinforcement Learning and Prediction-Based Lookahead Policy for Vehicle Repositioning in Online Ride-Hailing Systems. IEEE Trans. Intell. Transp. Syst. 25(2): 1846-1856 (2024)- 2023
- [j10]Xiong-Hui Chen, Fan-Ming Luo, Yang Yu, Qingyang Li, Zhiwei Qin, Wenjie Shang, Jieping Ye:
Offline Model-Based Adaptable Policy Learning for Decision-Making in Out-of-Support Regions. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15260-15274 (2023) - [j9]Yongxin Tong, Dingyuan Shi, Yi Xu, Weifeng Lv, Zhiwei Qin, Xiaocheng Tang:
Combinatorial Optimization Meets Reinforcement Learning: Effective Taxi Order Dispatching at Large-Scale. IEEE Trans. Knowl. Data Eng. 35(10): 9812-9823 (2023) - [c28]Alex Chin, Zhiwei (Tony) Qin:
A Unified Representation Framework for Rideshare Marketplace Equilibrium and Efficiency. SIGSPATIAL/GIS 2023: 38:1-38:11 - [c27]Xiong-Hui Chen, Bowei He, Yang Yu, Qingyang Li, Zhiwei Tony Qin, Wenjie Shang, Jieping Ye, Chen Ma:
Sim2Rec: A Simulator-based Decision-making Approach to Optimize Real-World Long-term User Engagement in Sequential Recommender Systems. ICDE 2023: 3389-3402 - [c26]Zhiwei (Tony) Qin, Rui Song, Jieping Ye, Hongtu Zhu, Michael I. Jordan:
KDD-2023 Workshop on Decision Intelligence and Analytics for Online Marketplaces. KDD 2023: 5878-5879 - [i17]Xiong-Hui Chen, Bowei He, Yang Yu, Qingyang Li, Zhiwei Tony Qin, Wenjie Shang, Jieping Ye, Chen Ma:
Sim2Rec: A Simulator-based Decision-making Approach to Optimize Real-World Long-term User Engagement in Sequential Recommender Systems. CoRR abs/2305.04832 (2023) - 2022
- [j8]Zhiwei (Tony) Qin, Liangjie Hong, Rui Song, Hongtu Zhu, Mohammed Korayem, Haiyan Luo, Michael I. Jordan:
KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond. SIGKDD Explor. 24(2): 78-80 (2022) - [c25]Tao Huang, Qingyang Li, Zhiwei Qin:
Multiple Tiered Treatments Optimization with Causal Inference on Response Distribution. IEEE Big Data 2022: 962-971 - [c24]Soheil Sadeghi Eshkevari, Xiaocheng Tang, Zhiwei Qin, Jinhan Mei, Cheng Zhang, Qianying Meng, Jia Xu:
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace. KDD 2022: 3838-3848 - [c23]Zhiwei (Tony) Qin, Liangjie Hong, Rui Song, Hongtu Zhu, Mohammed Korayem, Haiyan Luo, Michael I. Jordan:
Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond. KDD 2022: 4898-4899 - [i16]Soheil Sadeghi Eshkevari, Xiaocheng Tang, Zhiwei Qin, Jinhan Mei, Cheng Zhang, Qianying Meng, Jia Xu:
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace. CoRR abs/2202.05118 (2022) - [i15]Yanqiu Wu, Qingyang Li, Zhiwei Tony Qin:
Spatio-temporal Incentives Optimization for Ride-hailing Services with Offline Deep Reinforcement Learning. CoRR abs/2211.03240 (2022) - 2021
- [j7]Wenjie Shang, Qingyang Li, Zhiwei (Tony) Qin, Yang Yu, Yiping Meng, Jieping Ye:
Partially observable environment estimation with uplift inference for reinforcement learning based recommendation. Mach. Learn. 110(9): 2603-2640 (2021) - [c22]Chunyi Liu, Hao Feng, Jiang Xu, Zhiwei Tony Qin, Hongtu Zhu:
Optimizing Bike-Share Repositioning: Networked Inventory Management with Spatiotemporal Modeling. IEEE BigData 2021: 1438-1448 - [c21]Fan Zhou, Chenfan Lu, Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Jieping Ye, Hongtu Zhu:
Multi-Objective Distributional Reinforcement Learning for Large-Scale Order Dispatching. ICDM 2021: 1541-1546 - [c20]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. ITSC 2021: 2447-2454 - [c19]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. KDD 2021: 3605-3615 - [c18]Xiong-Hui Chen, Yang Yu, Qingyang Li, Fan-Ming Luo, Zhiwei (Tony) Qin, Wenjie Shang, Jieping Ye:
Offline Model-based Adaptable Policy Learning. NeurIPS 2021: 8432-8443 - [i14]Yan Jiao, Xiaocheng Tang, Zhiwei (Tony) Qin, Shuaiji Li, Fan Zhang, Hongtu Zhu, Jieping Ye:
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning. CoRR abs/2103.04555 (2021) - [i13]Zhiwei (Tony) Qin, Hongtu Zhu, Jieping Ye:
Reinforcement Learning for Ridesharing: A Survey. CoRR abs/2105.01099 (2021) - [i12]Xiaocheng Tang, Fan Zhang, Zhiwei (Tony) Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye:
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms. CoRR abs/2105.08791 (2021) - [i11]Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. CoRR abs/2106.04493 (2021) - 2020
- [j6]Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Fan Zhang, Zhe Xu, Hongtu Zhu, Jieping Ye:
Ride-Hailing Order Dispatching at DiDi via Reinforcement Learning. INFORMS J. Appl. Anal. 50(5): 272-286 (2020) - [c17]Mengyue Yang, Qingyang Li, Zhiwei (Tony) Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. WWW 2020: 292-302 - [i10]Mengyue Yang, Qingyang Li, Zhiwei (Tony) Qin, Jieping Ye:
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation. CoRR abs/2004.01136 (2020)
2010 – 2019
- 2019
- [c16]Tao Huang, Yintai Ma, Zhiwei (Tony) Qin, Jianfeng Zheng, Henry X. Liu, Hongtu Zhu, Jieping Ye:
Origin-destination Flow Prediction with Vehicle Trajectory Data and Semi-supervised Recurrent Neural Network. IEEE BigData 2019: 1450-1459 - [c15]Jiarui Jin, Ming Zhou, Weinan Zhang, Minne Li, Zilong Guo, Zhiwei (Tony) Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye:
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms. CIKM 2019: 1983-1992 - [c14]Ming Zhou, Jiarui Jin, Weinan Zhang, Zhiwei (Tony) Qin, Yan Jiao, Chenxi Wang, Guobin Wu, Yong Yu, Jieping Ye:
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching. CIKM 2019: 2645-2653 - [c13]Haipeng Chen, Yan Jiao, Zhiwei (Tony) Qin, Xiaocheng Tang, Hao Li, Bo An, Hongtu Zhu, Jieping Ye:
InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms. ICDM 2019: 61-70 - [c12]John Holler, Risto Vuorio, Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem. ICDM 2019: 1090-1095 - [c11]Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Fan Zhang, Chenxi Wang, Qun (Tracy) Li:
Deep Reinforcement Learning for Ride-sharing Dispatching and Repositioning. IJCAI 2019: 6566-6568 - [c10]Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye:
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. KDD 2019: 566-576 - [c9]Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. KDD 2019: 1780-1790 - [c8]Zhiwei (Tony) Qin, Jian Tang, Jieping Ye:
Deep Reinforcement Learning with Applications in Transportation. KDD 2019: 3201-3202 - [c7]Shuaiji Li, Tao Huang, Zhiwei Qin, Fanfang Zhang, Yinhong Chang:
Domain Generation Algorithms detection through deep neural network and ensemble. WWW (Companion Volume) 2019: 189-196 - [c6]Minne Li, Zhiwei (Tony) Qin, Yan Jiao, Yaodong Yang, Jun Wang, Chenxi Wang, Guobin Wu, Jieping Ye:
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning. WWW 2019: 983-994 - [i9]Minne Li, Zhiwei (Tony) Qin, Yan Jiao, Yaodong Yang, Zhichen Gong, Jun Wang, Chenxi Wang, Guobin Wu, Jieping Ye:
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning. CoRR abs/1901.11454 (2019) - [i8]Jiarui Jin, Ming Zhou, Weinan Zhang, Minne Li, Zilong Guo, Zhiwei (Tony) Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye:
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms. CoRR abs/1905.11353 (2019) - [i7]Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye:
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. CoRR abs/1907.06584 (2019) - [i6]Ming Zhou, Jiarui Jin, Weinan Zhang, Zhiwei (Tony) Qin, Yan Jiao, Chenxi Wang, Guobin Wu, Yong Yu, Jieping Ye:
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching. CoRR abs/1910.02591 (2019) - [i5]John Holler, Risto Vuorio, Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye:
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem. CoRR abs/1911.11260 (2019) - 2018
- [j5]Zhiwei (Tony) Qin, John Bowman, Jagtej Bewli:
A Bayesian framework for large-scale geo-demand estimation in on-line retailing. Ann. Oper. Res. 263(1-2): 231-245 (2018) - [c5]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. IEEE BigData 2018: 1417-1426 - [c4]Zhaodong Wang, Zhiwei (Tony) Qin, Xiaocheng Tang, Jieping Ye, Hongtu Zhu:
Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching. ICDM 2018: 617-626 - [c3]Zhiwei (Tony) Qin, Chengxiang Zhuo, Wei Tan, Jun Xie, Jieping Ye:
Large-Scale Targeted Marketing by Supervised PageRank with Seeds. MLDM (2) 2018: 409-424 - [i4]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. CoRR abs/1811.04345 (2018) - 2017
- [i3]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip. CoRR abs/1710.04350 (2017) - 2015
- [j4]Zhiwei (Tony) Qin, Donald Goldfarb, Shiqian Ma:
An alternating direction method for total variation denoising. Optim. Methods Softw. 30(3): 594-615 (2015) - [c2]Long He, Zhiwei (Tony) Qin, Jagtej Bewli:
Low-Rank Tensor Recovery for Geo-Demand Estimation in Online Retailing. INNS Conference on Big Data 2015: 239-247 - 2014
- [j3]Donald Goldfarb, Zhiwei (Tony) Qin:
Robust Low-Rank Tensor Recovery: Models and Algorithms. SIAM J. Matrix Anal. Appl. 35(1): 225-253 (2014) - [c1]Zhiwei (Tony) Qin, Xiaocheng Tang, Ioannis Akrotirianakis, Amit Chakraborty:
HIPAD - A Hybrid Interior-Point Alternating Direction Algorithm for Knowledge-Based SVM and Feature Selection. LION 2014: 324-340 - [i2]Zhiwei (Tony) Qin, Xiaocheng Tang, Ioannis Akrotirianakis, Amit Chakraborty:
HIPAD - A Hybrid Interior-Point Alternating Direction algorithm for knowledge-based SVM and feature selection. CoRR abs/1411.4286 (2014) - 2013
- [b1]Zhiwei (Tony) Qin:
Optimization Algorithms for Structured Machine Learning and Image Processing Problems. Columbia University, USA, 2013 - [j2]Zhiwei (Tony) Qin, Katya Scheinberg, Donald Goldfarb:
Efficient block-coordinate descent algorithms for the Group Lasso. Math. Program. Comput. 5(2): 143-169 (2013) - 2012
- [j1]Zhiwei (Tony) Qin, Donald Goldfarb:
Structured Sparsity via Alternating Direction Methods. J. Mach. Learn. Res. 13: 1435-1468 (2012) - 2011
- [i1]Zhiwei (Tony) Qin, Donald Goldfarb:
Structured Sparsity via Alternating Directions Methods. CoRR abs/1105.0728 (2011)
Coauthor Index
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