252 citations · 392 across the 19 of their papers we have counts for
13 papers · 1 filter
ChronoSelect: Robust Learning with Noisy Labels via Dynamics Temporal Memory
Jianchao Wang, Qingfeng Li, Pengcheng Zheng +2
Training deep neural networks on real-world datasets is often hampered by the presence of noisy labels, which can be memorized by over-parameterized models, leading to significant…
Dual-Optimized Adaptive Graph Reconstruction for Multi-View Graph Clustering
Zichen Wen, Tianyi Wu, Yazhou Ren +4
Multi-view clustering is an important machine learning task for multi-media data, encompassing various domains such as images, videos, and texts. Moreover, with the growing abundan…
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…
Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering
Zichen Wen, Yawen Ling, Yazhou Ren +5
Recently there is a growing focus on graph data, and multi-view graph clustering has become a popular area of research interest. Most of the existing methods are only applicable to…
A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective
Chenhang Cui, Yazhou Ren, Jingyu Pu +5
Multi-view clustering (MVC) is a popular technique for improving clustering performance using various data sources. However, existing methods primarily focus on acquiring consisten…
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…
Deep Multi-View Subspace Clustering with Anchor Graph
Chenhang Cui, Yazhou Ren, Jingyu Pu +2
Deep multi-view subspace clustering (DMVSC) has recently attracted increasing attention due to its promising performance. However, existing DMVSC methods still have two issues: (1)…
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…
Deep Embedded Multi-View Clustering via Jointly Learning Latent Representations and Graphs
Zongmo Huang, Yazhou Ren, Xiaorong Pu +1
With the representation learning capability of the deep learning models, deep embedded multi-view clustering (MVC) achieves impressive performance in many scenarios and has become…
Non-Linear Fusion for Self-Paced Multi-View Clustering
Zongmo Huang, Yazhou Ren, Xiaorong Pu +1
With the advance of the multi-media and multi-modal data, multi-view clustering (MVC) has drawn increasing attentions recently. In this field, one of the most crucial challenges is…
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…
Multi-graph Fusion for Multi-view Spectral Clustering
Zhao Kang, Guoxin Shi, Shudong Huang +4
A panoply of multi-view clustering algorithms has been developed to deal with prevalent multi-view data. Among them, spectral clustering-based methods have drawn much attention and…