41 citations · 89 across the 10 of their papers we have counts for
10 papers
Semi-supervised Domain Adaptation in Graph Transfer Learning
Ziyue Qiao, Xiao Luo, Meng Xiao +3
As a specific case of graph transfer learning, unsupervised domain adaptation on graphs aims for knowledge transfer from label-rich source graphs to unlabeled target graphs. Howeve…
Traceable Group-Wise Self-Optimizing Feature Transformation Learning: A Dual Optimization Perspective
Meng Xiao, Dongjie Wang, Min Wu +4
Feature transformation aims to reconstruct an effective representation space by mathematically refining the existing features. It serves as a pivotal approach to combat the curse o…
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
Yansong Ning, Hao Liu, Hao Wang +2
Accurate Urban SpatioTemporal Prediction (USTP) is of great importance to the development and operation of the smart city. As an emerging building block, multi-sourced urban data a…
TriMLP: Revenge of a MLP-like Architecture in Sequential Recommendation
Yiheng Jiang, Yuanbo Xu, Yongjian Yang +3
In this paper, we present a MLP-like architecture for sequential recommendation, namely TriMLP, with a novel Triangular Mixer for cross-token communications. In designing Triangula…
Hierarchical Interdisciplinary Topic Detection Model for Research Proposal Classification
Meng Xiao, Ziyue Qiao, Yanjie Fu +5
The peer merit review of research proposals has been the major mechanism for deciding grant awards. However, research proposals have become increasingly interdisciplinary. It has b…
Self-Optimizing Feature Transformation
Meng Xiao, Dongjie Wang, Min Wu +4
Feature transformation aims to extract a good representation (feature) space by mathematically transforming existing features. It is crucial to address the curse of dimensionality,…
Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity
Jiangmeng Li, Wenwen Qiang, Changwen Zheng +4
While self-supervised learning techniques are often used to mining implicit knowledge from unlabeled data via modeling multiple views, it is unclear how to perform effective repres…
Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction
Liangzhe Han, Xiaojian Ma, Leilei Sun +4
Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society. Among them, the pairwise Origin-Destination (OD) demand…
Feature and Instance Joint Selection: A Reinforcement Learning Perspective
Wei Fan, Kunpeng Liu, Hao Liu +3
Feature selection and instance selection are two important techniques of data processing. However, such selections have mostly been studied separately, while existing work towards…
Reinforced Imitative Graph Learning for Mobile User Profiling
Dongjie Wang, Pengyang Wang, Yanjie Fu +3
Mobile user profiling refers to the efforts of extracting users' characteristics from mobile activities. In order to capture the dynamic varying of user characteristics for generat…