185 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Electronic Science and Technology of ChinaCN23 papers
- Sichuan UniversityCN18 papers
- University of Hong KongHK11 papers
- London School of Economics and Political ScienceGB9 papers
- Southwest Jiaotong UniversityCN9 papers
- University of GroningenNL8 papers
- Hong Kong Polytechnic UniversityHK6 papers
- The University of MelbourneAU6 papers
- University of PittsburghUS6 papers
- Chengdu UniversityCN5 papers
- Chinese Academy of SciencesCN5 papers
- Hong Kong University of Science and TechnologyHK5 papers
10 papers · 1 filter
Traceable Latent Variable Discovery Based on Multi-Agent Collaboration
Huaming Du, Tao Hu, Yijie Huang +5
Revealing the underlying causal mechanisms in the real world is crucial for scientific and technological progress. Despite notable advances in recent decades, the lack of high-qual…
ErrorEraser: Unlearning Data Bias for Improved Continual Learning
Xuemei Cao, Hanlin Gu, Xin Yang +4
Continual Learning (CL) primarily aims to retain knowledge to prevent catastrophic forgetting and transfer knowledge to facilitate learning new tasks. Unlike traditional methods, w…
RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation
Junyu Chen, Long Shi, Badong Chen
Graph Neural Networks (GNNs) have exhibited remarkable efficacy in learning from multi-view graph data. In the framework of multi-view graph neural networks, a critical challenge l…
Personalized Federated Continual Learning via Multi-granularity Prompt
Hao Yu, Xin Yang, Xin Gao +4
Personalized Federated Continual Learning (PFCL) is a new practical scenario that poses greater challenges in sharing and personalizing knowledge. PFCL not only relies on knowledge…
Federated Continual Learning via Knowledge Fusion: A Survey
Xin Yang, Hao Yu, Xin Gao +3
Data privacy and silos are nontrivial and greatly challenging in many real-world applications. Federated learning is a decentralized approach to training models across multiple loc…
Enhanced Latent Multi-view Subspace Clustering
Long Shi, Lei Cao, Jun Wang +1
Latent multi-view subspace clustering has been demonstrated to have desirable clustering performance. However, the original latent representation method vertically concatenates the…
Asymmetric Graph Representation Learning
Zhuo Tan, Bin Liu, Guosheng Yin
Despite the enormous success of graph neural networks (GNNs), most existing GNNs can only be applicable to undirected graphs where relationships among connected nodes are two-way s…
Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning
Zhi Chen, Jiang Duan, Li Kang +1
Anomaly detection has wide applications in machine intelligence but is still a difficult unsolved problem. Major challenges include the rarity of labeled anomalies and it is a clas…
Adaptive Graph-based Generalized Regression Model for Unsupervised Feature Selection
Yanyong Huang, Zongxin Shen, Fuxu Cai +2
Unsupervised feature selection is an important method to reduce dimensions of high dimensional data without labels, which is benefit to avoid ``curse of dimensionality'' and improv…
Multi-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix
Weixuan Liang, Sihang Zhou, Jian Xiong +5
Multi-view spectral clustering can effectively reveal the intrinsic cluster structure among data by performing clustering on the learned optimal embedding across views. Though demo…