Segui
Zhiwei (Tony) Qin
Zhiwei (Tony) Qin
Altri nomiZhiwei Qin, Tony Qin
Principal Scientist, Lyft Rideshare Labs
Email verificata su caa.columbia.edu - Home page
Titolo
Citata da
Citata da
Anno
Robust low-rank tensor recovery: Models and algorithms
D Goldfarb, Z Qin
SIAM Journal on Matrix Analysis and Applications 35 (1), 225-253, 2014
4092014
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning
M Li, Z Qin, Y Jiao, Y Yang, J Wang, C Wang, G Wu, J Ye
WWW '19 The World Wide Web Conference, 983-994, 2019
2602019
Efficient block-coordinate descent algorithms for the group lasso
Z Qin, K Scheinberg, D Goldfarb
Mathematical Programming Computation 5 (2), 143-169, 2013
2292013
A deep value-network based approach for multi-driver order dispatching
X Tang, Z Qin, F Zhang, Z Wang, Z Xu, Y Ma, H Zhu, J Ye
Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019
1592019
Optimizing taxi carpool policies via reinforcement learning and spatio-temporal mining
I Jindal, ZT Qin, X Chen, M Nokleby, J Ye
2018 IEEE International Conference on Big Data (Big Data), 1417-1426, 2018
140*2018
Deep reinforcement learning with knowledge transfer for online rides order dispatching
Z Wang, Z Qin, X Tang, J Ye, H Zhu
2018 IEEE International Conference on Data Mining (ICDM), 617-626, 2018
1322018
Deep reinforcement learning for multi-driver vehicle dispatching and repositioning problem
J Holler, R Vuorio, Z Qin, X Tang, Y Jiao, T Jin, S Singh, C Wang, J Ye
2019 IEEE International Conference on Data Mining (ICDM), 1090-1095, 2019
1102019
Ride-hailing order dispatching at didi via reinforcement learning
Z Qin, X Tang, Y Jiao, F Zhang, Z Xu, H Zhu, J Ye
INFORMS Journal on Applied Analytics 50 (5), 272-286, 2020
1042020
Coride: joint order dispatching and fleet management for multi-scale ride-hailing platforms
J Jin, M Zhou, W Zhang, M Li, Z Guo, Z Qin, Y Jiao, X Tang, C Wang, ...
Proceedings of the 28th ACM international conference on information and …, 2019
1012019
Multi-agent reinforcement learning for order-dispatching via order-vehicle distribution matching
M Zhou, J Jin, W Zhang, Z Qin, Y Jiao, C Wang, G Wu, Y Yu, J Ye
Proceedings of the 28th ACM International Conference on Information and …, 2019
892019
Structured sparsity via alternating direction methods
Z Qin, D Goldfarb
The Journal of Machine Learning Research 13 (1), 1373-1406, 2012
762012
An alternating direction method for total variation denoising
Z Qin, D Goldfarb, S Ma
Optimization Methods and Software, 2011
62*2011
Environment reconstruction with hidden confounders for reinforcement learning based recommendation
W Shang, Y Yu, Q Li, Z Qin, Y Meng, J Ye
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
482019
Real-world ride-hailing vehicle repositioning using deep reinforcement learning
Y Jiao, X Tang, ZT Qin, S Li, F Zhang, H Zhu, J Ye
Transportation Research Part C: Emerging Technologies 130, 103289, 2021
412021
Inventory mirroring in a heterogeneous fulfillment network
Z Qin
US Patent 10,650,344, 2020
402020
Reinforcement learning for ridesharing: An extended survey
ZT Qin, H Zhu, J Ye
Transportation Research Part C: Emerging Technologies 144, 103852, 2022
352022
Multi-modal graph interaction for multi-graph convolution network in urban spatiotemporal forecasting
L Zhang, X Geng, Z Qin, H Wang, X Wang, Y Zhang, J Liang, G Wu, ...
Sustainability 14 (19), 12397, 2022
352022
Sparse reinforcement learning via convex optimization
Z Qin, W Li, F Janoos
International Conference on Machine Learning, 424-432, 2014
332014
Value function is all you need: A unified learning framework for ride hailing platforms
X Tang, F Zhang, Z Qin, Y Wang, D Shi, B Song, Y Tong, H Zhu, J Ye
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
292021
InBEDE: Integrating contextual bandit with TD learning for joint pricing and dispatch of ride-hailing platforms
H Chen, Y Jiao, Z Qin, X Tang, H Li, B An, H Zhu, J Ye
2019 IEEE International Conference on Data Mining (ICDM), 61-70, 2019
262019
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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