85 citations
- University of California, BerkeleyUS3 papers
- Beihang UniversityCN2 papers
- Nankai UniversityCN2 papers
- Peking UniversityCN2 papers
- Renmin University of ChinaCN2 papers
- University of Chinese Academy of SciencesCN2 papers
- University of MichiganUS2 papers
- Africa Nazarene UniversityKE1 paper
- Beijing University of Posts and TelecommunicationsCN1 paper
- Carleton UniversityCA1 paper
- Center for Excellence in Brain Science and Intelligence TechnologyCN1 paper
- Huazhong University of Science and TechnologyCN1 paper
6 papers · 1 filter
A Deep Value-network Based Approach for Multi-Driver Order Dispatching
Xiaocheng Tang, Zhiwei Qin, Fan Zhang +5
Recent works on ride-sharing order dispatching have highlighted the importance of taking into account both the spatial and temporal dynamics in the dispatching process for improvin…
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
Mengyue Yang, Qingyang Li, Zhiwei Qin +1
Contextual multi-armed bandit (MAB) achieves cutting-edge performance on a variety of problems. When it comes to real-world scenarios such as recommendation system and online adver…
An Attention-based Graph Neural Network for Heterogeneous Structural Learning
Huiting Hong, Hantao Guo, Yucheng Lin +3
In this paper, we focus on graph representation learning of heterogeneous information network (HIN), in which various types of vertices are connected by various types of relations.…
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem
John Holler, Risto Vuorio, Zhiwei Qin +6
Order dispatching and driver repositioning (also known as fleet management) in the face of spatially and temporally varying supply and demand are central to a ride-sharing platform…
Multi-source Distilling Domain Adaptation
Sicheng Zhao, Guangzhi Wang, Shanghang Zhang +7
Deep neural networks suffer from performance decay when there is domain shift between the labeled source domain and unlabeled target domain, which motivates the research on domain…
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
Wenjie Shang, Yang Yu, Qingyang Li +3
Reinforcement learning aims at searching the best policy model for decision making, and has been shown powerful for sequential recommendations. The training of the policy by reinfo…