26 citations · 39 across the 4 of their papers we have counts for
7 papers
Learning Disentangled Representations for Generalized Multi-view Clustering
Xin Zou, Ruimeng Liu, Chang Tang +4
Multi-View Clustering (MVC) has gained significant attention for its ability to leverage complementary information across diverse views. However, existing deep MVC methods often st…
Generalized Deep Multi-view Clustering via Causal Learning with Partially Aligned Cross-view Correspondence
Xihong Yang, Siwei Wang, Jiaqi Jin +6
Multi-view clustering (MVC) aims to explore the common clustering structure across multiple views. Many existing MVC methods heavily rely on the assumption of view consistency, whe…
Intra-view and Inter-view Correlation Guided Multi-view Novel Class Discovery
Xinhang Wan, Jiyuan Liu, Qian Qu +6
In this paper, we address the problem of novel class discovery (NCD), which aims to cluster novel classes by leveraging knowledge from disjoint known classes. While recent advances…
Deep Incomplete Multi-view Clustering with Distribution Dual-Consistency Recovery Guidance
Jiaqi Jin, Siwei Wang, Zhibin Dong +4
Multi-view clustering leverages complementary representations from diverse sources to enhance performance. However, real-world data often suffer incomplete cases due to factors lik…
Active-Passive Federated Learning for Vertically Partitioned Multi-view Data
Jiyuan Liu, Siqi Wang, Xinhang Wan +4
Vertical federated learning is a natural and elegant approach to integrate multi-view data vertically partitioned across devices (clients) while preserving their privacies. Apart f…
FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction
Muhao Xu, Zhenfeng Zhu, Youru Li +4
Multimodal electronic health record (EHR) data can offer a holistic assessment of a patient's health status, supporting various predictive healthcare tasks. Recently, several studi…
A Survey of Deep Graph Clustering: Taxonomy, Challenge, Application, and Open Resource
Yue Liu, Jun Xia, Sihang Zhou +7
Graph clustering, which aims to divide nodes in the graph into several distinct clusters, is a fundamental yet challenging task. Benefiting from the powerful representation capabil…