activity
20172022
most citedA Neural Influence Diffusion Model for Social Recommendation

30 citations · 126 across the 29 of their papers we have counts for

collaborators

20 papers

cs.CV2021

Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning

Dongjie Wang, Kunpeng Liu, Pauline Johnson +3

Urban planning designs land-use configurations and can benefit building livable, sustainable, safe communities. Inspired by image generation, deep urban planning aims to leverage d…

cs.LG2021

Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy

Kunpeng Liu, Pengfei Wang, Dongjie Wang +3

In this paper, we propose a single-agent Monte Carlo based reinforced feature selection (MCRFS) method, as well as two efficiency improvement strategies, i.e., early stopping (ES)…

cs.LG2021

Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning

Dongjie Wang, Kunpeng Liu, David Mohaisen +3

Automated characterization of spatial data is a kind of critical geographical intelligence. As an emerging technique for characterization, Spatial Representation Learning (SRL) use…

cs.AI20212 cited

Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective

Dongjie Wang, Pengyang Wang, Kunpeng Liu +3

In this paper, we study the problem of mobile user profiling, which is a critical component for quantifying users' characteristics in the human mobility modeling pipeline. Human mo…

cs.LG202023 cited

Coupled Layer-wise Graph Convolution for Transportation Demand Prediction

Junchen Ye, Leilei Sun, Bowen Du +2

Graph Convolutional Network (GCN) has been widely applied in transportation demand prediction due to its excellent ability to capture non-Euclidean spatial dependence among station…

cs.LG20202 cited

Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop

Wei Fan, Kunpeng Liu, Hao Liu +3

We study the problem of balancing effectiveness and efficiency in automated feature selection. After exploring many feature selection methods, we observe a computational dilemma: 1…