Results 61 to 70 of about 169,617 (164)
Multi-view Graph Clustering Algorithm Based on Dual Contrastive Learning and Hard Sample Mining [PDF]
Jisuanji gongchengAs a key research direction in the field of graph mining, graph clustering aims to discover substructures or node groups with similarities from graph data and classify them into the same cluster.
QIAN Lifeng, LI Jing, ZOU Xuxi, CHEN Yu, GU Yalin, WEI Xunhu
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Reliable Conflictive Multi-View Learning
Proceedings of the AAAI Conference on Artificial IntelligenceMulti-view learning aims to combine multiple features to achieve more comprehensive descriptions of data. Most previous works assume that multiple views are strictly aligned. However, real-world multi-view data may contain low-quality conflictive instances, which show conflictive information in different views.
Xu, Cai +5 more
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Journal of King Saud University: Computer and Information SciencesRecently, multi-view multi-label learning has gained significant attention due to its applicability in various domains. However, due to the limitations of data collection and the subjectivity of manual labeling, multi-view multi-label learning often ...
Linqian Yang +4 more
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Incomplete multi-view partial multi-label classification via deep semantic structure preservation
Complex & Intelligent SystemsRecent advances in multi-view multi-label learning are often hampered by the prevalent challenges of incomplete views and missing labels, common in real-world data due to uncertainties in data collection and manual annotation.
Chaoran Li +4 more
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Privacy-Preserving Decentralized Federated Multi-View Clustering [PDF]
Jisuanji gongchengIn the era of big data, multi-view data exist in large quantities, and most existing multi-view clustering methods aggregate the data of all views for learning.
LEI Yifan, CHEN Xiaohong
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Semi-Supervised Multi-View Ensemble Learning Based On Extracting Cross-View Correlation
Advances in Electrical and Computer Engineering, 2016 Correlated information between different views incorporate useful for learning in multi view data. Canonical correlation analysis (CCA) plays important role to extract these information.
ZALL, R., KEYVANPOUR, M. R.
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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.
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Retargeted Multi-View Feature Learning With Separate and Shared Subspace Uncovering
IEEE Access, 2017 Multi-view feature learning aims at improving the performances of learning tasks, by fusing various kinds of features (views), such as heterogeneous features and/or homogeneous features.
Guo-Sen Xie +5 more
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Multi-view Sentence Representation Learning
, 2018 Multi-view learning can provide self-supervision when different views are available of the same data. The distributional hypothesis provides another form of useful self-supervision from adjacent sentences which are plentiful in large unlabelled corpora. Motivated by the asymmetry in the two hemispheres of the human brain as well as the observation that
Tang, Shuai, de Sa, Virginia R.
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Multi-view clustering via consensus coefficient matrix and separate segmentation matrices
Journal of Information and TelecommunicationIn recent years, achieving data from different sources and different views has caused to have many multi-view data sets. Among multi-view learning methods, multi-view clustering has been considered as an appropriate method to analyse these data by many ...
Fatemeh Sadjadi +2 more
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