activity
20192023
most citedA Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

262 citations · 382 across the 23 of their papers we have counts for

collaborators

31 papers

cs.AI20221 cited

Rethinking Graph Convolutional Networks in Knowledge Graph Completion

Zhanqiu Zhang, Jie Wang, Jieping Ye +1

Graph convolutional networks (GCNs) -- which are effective in modeling graph structures -- have been increasingly popular in knowledge graph completion (KGC). GCN-based KGC models…

cs.LG20214 cited

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

Xiaocheng Tang, Fan Zhang, Zhiwei Qin +6

Large ride-hailing platforms, such as DiDi, Uber and Lyft, connect tens of thousands of vehicles in a city to millions of ride demands throughout the day, providing great promises…

math.OC20212 cited

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

Fan Zhou, Shikai Luo, Xiaohu Qie +2

How to dynamically measure the local-to-global spatio-temporal coherence between demand and supply networks is a fundamental task for ride-sourcing platforms, such as DiDi. Such co…

cs.LG2021

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

Yan Jiao, Xiaocheng Tang, Zhiwei Qin +4

We present a new practical framework based on deep reinforcement learning and decision-time planning for real-world vehicle repositioning on ride-hailing (a type of mobility-on-dem…

math.NA20205 cited

Successive Projection for Solving Systems of Nonlinear Equations/Inequalities

Wen-Jun Zeng, Jieping Ye

Solving large-scale systems of nonlinear equations/inequalities is a fundamental problem in computing and optimization. In this paper, we propose a generic successive projection (S…

cs.CV20202 cited

Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation

Bingyu Liu, Yuhong Guo, Jieping Ye +1

Recent domain adaptation methods have demonstrated impressive improvement on unsupervised domain adaptation problems. However, in the semi-supervised domain adaptation (SSDA) setti…