271 citations · 547 across the 9 of their papers we have counts for
11 papers
Understanding and Mitigating Under-Confidence in GNNs from the Final Layer
Jincheng Huang, Jie Xu, Xiaoshuang Shi +3
Graph Neural Networks (GNNs) have demonstrated remarkable effectiveness on graph-based tasks. However, their predictive confidence is often miscalibrated, typically exhibiting unde…
Robust Multi-View Learning via Representation Fusion of Sample-Level Attention and Alignment of Simulated Perturbation
Jie Xu, Na Zhao, Gang Niu +2
Recently, multi-view learning (MVL) has garnered significant attention due to its ability to fuse discriminative information from multiple views. However, real-world multi-view dat…
Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views
Xinyue Chen, Yazhou Ren, Jie Xu +3
Recently, federated multi-view clustering (FedMVC) has emerged to explore cluster structures in multi-view data distributed on multiple clients. Existing approaches often assume th…
Federated Deep Multi-View Clustering with Global Self-Supervision
Xinyue Chen, Jie Xu, Yazhou Ren +5
Federated multi-view clustering has the potential to learn a global clustering model from data distributed across multiple devices. In this setting, label information is unknown an…
Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios
Jie Xu, Yazhou Ren, Xiaolong Wang +4
Multi-view clustering (MVC) aims at exploring category structures among multi-view data in self-supervised manners. Multiple views provide more information than single views and th…
Deep Clustering: A Comprehensive Survey
Yazhou Ren, Jingyu Pu, Zhimeng Yang +5
Cluster analysis plays an indispensable role in machine learning and data mining. Learning a good data representation is crucial for clustering algorithms. Recently, deep clusterin…
Variational Graph Generator for Multi-View Graph Clustering
Jianpeng Chen, Yawen Ling, Jie Xu +6
Multi-view graph clustering (MGC) methods are increasingly being studied due to the explosion of multi-view data with graph structural information. The critical point of MGC is to…
Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering
Jie Xu, Yazhou Ren, Huayi Tang +4
Multi-view clustering, a long-standing and important research problem, focuses on mining complementary information from diverse views. However, existing works often fuse multiple v…
Multi-level Feature Learning for Contrastive Multi-view Clustering
Jie Xu, Huayi Tang, Yazhou Ren +3
Multi-view clustering can explore common semantics from multiple views and has attracted increasing attention. However, existing works punish multiple objectives in the same featur…
Self-Supervised Discriminative Feature Learning for Deep Multi-View Clustering
Jie Xu, Yazhou Ren, Huayi Tang +6
Multi-view clustering is an important research topic due to its capability to utilize complementary information from multiple views. However, there are few methods to consider the…
Deep Embedded Multi-view Clustering with Collaborative Training
Jie Xu, Yazhou Ren, Guofeng Li +3
Multi-view clustering has attracted increasing attentions recently by utilizing information from multiple views. However, existing multi-view clustering methods are either with hig…