328 citations
- Sun Yat-sen UniversityCN37 papers
- Nanyang Technological UniversitySG26 papers
- University of Hong KongHK25 papers
- Chinese University of Hong Kong, ShenzhenCN24 papers
- South China University of TechnologyCN24 papers
- National University of SingaporeSG22 papers
- Tel Aviv UniversityIL19 papers
- South China Agricultural UniversityCN18 papers
- Chinese Academy of SciencesCN17 papers
- Foshan UniversityCN12 papers
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- University of MacauMO12 papers
38 papers · 1 filter
Resource-Efficient Pruning for Transformer via Low-Rank Importance Estimation
Peng Liu, Huibing Zeng, Yiqun Zhang +2
With the rapid development of large-scale pre-trained language models based on Transformer architectures, their high computational and memory costs have become a major obstacle to…
Learnable Weighting of Intra-Attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes
Yiqun Zhang, Yiu-ming Cheung
The success of categorical data clustering generally much relies on the distance metric that measures the dissimilarity degree between two objects. However, most of the existing cl…
Bridge the Gaps: Heterogeneous Attributed Graph Clustering via Quaternion Representation Learning
Xinxi Chen, Junyang Chen, Yiqun Zhang +2
Attributed graph clustering partitions nodes by jointly exploiting node attributes and graph topology. It remains challenging due to attribute heterogeneity and representation degr…
Hierarchical Reference Sets for Robust Unsupervised Detection of Scattered and Clustered Outliers
Yiqun Zhang, Zexi Tan, Xiaopeng Luo +1
Most real-world IoT data analysis tasks, such as clustering and anomaly event detection, are unsupervised and highly susceptible to the presence of outliers. In addition to sporadi…
Federated Hierarchical Clustering with Automatic Selection of Optimal Cluster Numbers
Yue Zhang, Chuanlong Qiu, Xinfa Liao +1
Federated Clustering (FC) is an emerging and promising solution in exploring data distribution patterns from distributed and privacy-protected data in an unsupervised manner. Exist…
Learning Unbiased Cluster Descriptors for Interpretable Imbalanced Concept Drift Detection
Yiqun Zhang, Zhanpei Huang, Mingjie Zhao +5
Unlabeled streaming data are usually collected to describe dynamic systems, where concept drift detection is a vital prerequisite to understanding the evolution of systems. However…