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2020 – today
- 2024
[j4]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
- [j3]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) - 2022
- [c16]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 - [i14]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) - [i13]Xiaocheng Tang, Soheil Sadeghi Eshkevari, Haoyu Chen, Weidan Wu, Wei Qian, Xiaoming Wang:
Golfer: Trajectory Prediction with Masked Goal Conditioning MnM Network. CoRR abs/2207.00738 (2022) - 2021
- [c15]Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. ICCV 2021: 10357-10366 - [c14]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 - [c13]Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
DrNAS: Dirichlet Neural Architecture Search. ICLR 2021 - [c12]Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh:
Rethinking Architecture Selection in Differentiable NAS. ICLR 2021 - [c11]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 - [i12]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) - [i11]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR abs/2103.15332 (2021) - [i10]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) - [i9]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) - [i8]Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh:
Rethinking Architecture Selection in Differentiable NAS. CoRR abs/2108.04392 (2021) - [i7]Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. CoRR abs/2108.08019 (2021) - 2020
- [j2]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) - [c10]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) 2020: 361-395 - [i6]Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh:
DrNAS: Dirichlet Neural Architecture Search. CoRR abs/2006.10355 (2020)
2010 – 2019
- 2019
- [c9]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 - [c8]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 - [c7]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 - [c6]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 - [c5]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 - [i5]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) - [i4]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
- [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 - 2016
- [j1]Katya Scheinberg, Xiaocheng Tang:
Practical inexact proximal quasi-Newton method with global complexity analysis. Math. Program. 160(1-2): 495-529 (2016) - 2014
- [c3]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 - [i3]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
- [c2]Bin He, Zhipeng Wang, Xiaocheng Tang, Qiang Lu:
Walking balance control for biped robot based on multi-sensor integration. ROBIO 2013: 425-430 - [i2]Xiaocheng Tang, Katya Scheinberg:
Efficiently Using Second Order Information in Large l1 Regularization Problems. CoRR abs/1303.6935 (2013) - [i1]Katya Scheinberg, Xiaocheng Tang:
Complexity of Inexact Proximal Newton methods. CoRR abs/1311.6547 (2013)
2000 – 2009
- 2008
- [c1]Hong Su, Bo Kang, Xiaocheng Tang:
Research and Implementation of Hybrid Tracking Techniques in Augmented Museum Tour System. Edutainment 2008: 636-643
Coauthor Index
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