Results 51 to 60 of about 134,390 (294)

Multi-view Contrastive Graph Clustering

CoRR, 2021
With the explosive growth of information technology, multi-view graph data have become increasingly prevalent and valuable. Most existing multi-view clustering techniques either focus on the scenario of multiple graphs or multi-view attributes. In this paper, we propose a generic framework to cluster multi-view attributed graph data.
Erlin Pan, Zhao Kang 0001
openaire   +3 more sources

AMCFCN: attentive multi-view contrastive fusion clustering net [PDF]

PeerJ Computer Science
Advances in deep learning have propelled the evolution of multi-view clustering techniques, which strive to obtain a view-common representation from multi-view datasets.
Huarun Xiao, Zhiyong Hong, Liping Xiong, Zhiqiang Zeng   +3 more
doaj   +2 more sources

Fairness-aware Multi-view Clustering

, 2023
In the era of big data, we are often facing the challenge of data heterogeneity and the lack of label information simultaneously. In the financial domain (e.g., fraud detection), the heterogeneous data may include not only numerical data (e.g., total debt and yearly income), but also text and images (e.g., financial statement and invoice images).
Lecheng Zheng, Yada Zhu, Jingrui He
openaire   +2 more sources

Multi-View Clustering in Latent Embedding Space [PDF]

, 2020
Previous multi-view clustering algorithms mostly partition the multi-view data in their original feature space, the efficacy of which heavily and implicitly relies on the quality of the original feature presentation. In light of this, this paper proposes
Huang, Ling, Wang, Chang-Dong, Huang, Dong, Chen, Man-Sheng   +3 more
core   +1 more source

Consensus Graph Learning for Multi-Task Multi-View Clustering [PDF]

Jisuanji gongcheng
Multi-view clustering focuses on mining consistency information between different views to improve performance. Most existing multi-view clustering algorithms focus on single-task multi-view clustering while ignoring the similarity of related tasks ...
WANG Lijuan, LI Xueyan, YIN Ming, HAO Zhifeng, CAI Ruichu, CHEN Wei, LIU Rui
doaj   +1 more source

Organoids in pediatric cancer research

FEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

Exploring Dynamic Hierarchical Fusion for Multi-View Clustering

IEEE Access
Multi-view clustering is effective at uncovering the latent structures within different views or modalities. However, existing approaches often oversimplify the problem by treating the contribution and granularity of information from all views as uniform,
Zhenshan Chen, Xuran Tian, Lizhen Gao, Gengbin Liao, Yang Shen, Kainan Zheng, Jianglin Fang   +6 more
doaj   +1 more source

Auto-Weighted Incomplete Multi-View Clustering

IEEE Access, 2020
Nowadays, multi-view clustering has attracted more and more attention, which provides a way to partition multi-view data into their corresponding clusters. Previous studies assume that each data instance appears in all views.
Wanyu Deng, Lixia Liu, Jianqiang Li, Yijun Lin   +3 more
doaj   +1 more source

Balanced Multi-view Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-view clustering (MvC) aims to integrate information from different views to enhance the capability of the model in capturing the underlying data structures. The widely used joint training paradigm in MvC is potentially not fully leverage the multi-view information, since the imbalanced and under-optimized view-specific features caused by the ...
Zhenglai Li, Jun Wang 0118, Chang Tang, Xinzhong Zhu, Wei Zhang 0049, Xinwang Liu 0002   +5 more
openaire   +2 more sources

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source