Results 61 to 70 of about 24,544,958 (149)

Multi-view data visualisation via manifold learning [PDF]

PeerJ Computer Science
Non-linear dimensionality reduction can be performed by manifold learning approaches, such as stochastic neighbour embedding (SNE), locally linear embedding (LLE) and isometric feature mapping (ISOMAP).
Theodoulos Rodosthenous, Vahid Shahrezaei, Marina Evangelou   +2 more
doaj   +2 more sources

Trusted Multi-View Deep Learning with Opinion Aggregation

, 2022
Multi-view deep learning is performed based on the deep fusion of data from multiple sources, i.e. data with multiple views. However, due to the property differences and inconsistency of data sources, the deep learning results based on the fusion of ...
Liu, Wei, Chen, Yufei, Denoeux, Thierry, Yue, Xiaodong   +3 more
core   +1 more source

One-step Multi-view Clustering Based on Diversity and Consistency [PDF]

Jisuanji gongcheng
With the development of data collection technology, multi-view data have become increasingly common. Compared to single-view data, multi-view data contain richer information, which is usually characterized by consistency and diversity information.
HU Aoran, CHEN Xiaohong
doaj   +1 more source

Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering

Advanced Intelligent Systems
Graph‐based incomplete multi‐view clustering (IMVC) methods have garnered significant attention due to their ability to capture intrinsic data structures in the presence of missing views.
Ping Hu, Chenggang Lu, Rui Zhang, Haijun Yan, Yesong Xu   +4 more
doaj   +1 more source

Multi-view Clustering: A Survey

Big Data Mining and Analytics, 2018
In the big data era, the data are generated from different sources or observed from different views. These data are referred to as multi-view data. Unleashing the power of knowledge in multi-view data is very important in big data mining and analysis ...
Yan Yang, Hao Wang
doaj   +1 more source

Unsupervised Learning from Multi-view Data [PDF]

, 2016
With the advance of technology, data are often with multiple modalities or coming from multiple sources. Such data are called multi-view data. Usually, multiple views provide complementary information for the semantically same data.
Weixiang Shao (7984739)
core   +3 more sources

PainFedMVL: A Federated Multi-View Learning Approach for Multi-Level Pain Recognition

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Pain is a critical clinical indicator in rehabilitation and neurological disorders, yet reliable multi-level recognition remains challenging due to subtle facial variations, inter-subject variability, and heterogeneous clinical data.
Daoyun Li, Zuyuan Yang, Shengli Xie
doaj   +1 more source

Biased Incomplete Multi-View Learning

Considering the ubiquitous phenomenon of missing views in multi-view data, incomplete multi-view learning is a crucial task in many applications. Existing methods usually follow an impute-then-predict strategy for handling this problem.
Zhao, Wei, Liu, Jinlong, Chen, Haishun, Xu, Cai, Guan, Ziyu   +4 more
core   +1 more source

Unbalanced Multi-view Deep Learning

, 2023
Most existing multi-view learning methods assume that the dimensions of different views are similar. In real-world applications, it is often the case that the dimension of a view may be extremely small compared with these of other views, resulting in an ...
Z Guan (13362369), Y Wu (808222), X Song (660803), W Zhao (7713869), Jianxin Li (13075998), Z Li (774829), C Xu (7775762)   +6 more
core   +1 more source

Multi-domain feature joint optimization based on multi-view learning for improving the EEG decoding. [PDF]

Front Hum Neurosci, 2023
Shi B, Yue Z, Yin S, Zhao J, Wang J.
europepmc   +1 more source