155 citations · 416 across the 26 of their papers we have counts for
9 papers · 1 filter
Multi-Dimensional Ability Diagnosis for Machine Learning Algorithms
Qi Liu, Zheng Gong, Zhenya Huang +5
Machine learning algorithms have become ubiquitous in a number of applications (e.g. image classification). However, due to the insufficient measurement of traditional metrics (e.g…
Multi-Temporal Relationship Inference in Urban Areas
Shuangli Li, Jingbo Zhou, Ji Liu +3
Finding multiple temporal relationships among locations can benefit a bunch of urban applications, such as dynamic offline advertising and smart public transport planning. While so…
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph
Chenguang Du, Kaichun Yao, Hengshu Zhu +3
Recent years have witnessed the rapid development of heterogeneous graph neural networks (HGNNs) in information retrieval (IR) applications. Many existing HGNNs design a variety of…
A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection
Congxi Xiao, Jingbo Zhou, Jizhou Huang +4
Urban villages (UVs) refer to the underdeveloped informal settlement falling behind the rapid urbanization in a city. Since there are high levels of social inequality and social ri…
Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification
Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +3
Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation i…
Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness
Dazhong Shen, Chuan Qin, Chao Wang +3
As one of the most popular generative models, Variational Autoencoder (VAE) approximates the posterior of latent variables based on amortized variational inference. However, when t…
Adversarial Neural Trip Recommendation
Linlang Jiang, Jingbo Zhou, Tong Xu +4
Trip recommender system, which targets at recommending a trip consisting of several ordered Points of Interest (POIs), has long been treated as an important application for many lo…
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction
Shuangli Li, Jingbo Zhou, Tong Xu +2
Recently many efforts have been devoted to applying graph neural networks (GNNs) to molecular property prediction which is a fundamental task for computational drug and material di…
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal
Weijia Zhang, Hao Liu, Lijun Zha +4
Real estate appraisal refers to the process of developing an unbiased opinion for real property's market value, which plays a vital role in decision-making for various players in t…