Results 71 to 80 of about 24,544,958 (149)

Adaptive fuzzy prototype learning with view-balanced multi-view embeddings for multi-behavior recommendation

Journal of King Saud University: Computer and Information Sciences
Multi-behavior recommender systems(RS) leverages diverse user actions(e.g. click, cart, purchase) to model preferences more comprehensively, yet it often suffers from noisy behavior signals and heterogeneous user–item representations.
Juan Liao, Zhe Liu, Aman Jantan, Narinderjit Singh Sawaran Singh, Wulfran Fendzi Mbasso, Himanshu Dhumras, Mehdi Hosseinzadeh   +6 more
doaj   +1 more source

Intra-View and Inter-View Supervised Correlation Analysis for Multi-View Feature Learning

, 2014
Multi-view feature learning is an attractive research topic with great practical success. Canonical correlation analysis (CCA) has become an important technique in multi-view learning, since it can fully utilize the inter-view correlation. In this paper,
Yang, Jing-Yu, Hu, Rui-Min, Jing, Xiao-Yuan, Liang, Chao, Wu, Shan-Shan, Zhu, Yang-Ping   +5 more
core   +1 more source

Multi-View Learning to Unravel the Different Levels Underlying Hepatitis B Vaccine Response. [PDF]

Vaccines (Basel), 2023
Affaticati F, Bartholomeus E, Mullan K, Damme PV, Beutels P, Ogunjimi B, Laukens K, Meysman P.   +7 more
europepmc   +1 more source

scPML: pathway-based multi-view learning for cell type annotation from single-cell RNA-seq data. [PDF]

Commun Biol, 2023
Du ZH, Hu WL, Li JQ, Shang X, You ZH, Chen ZZ, Huang YA.   +6 more
europepmc   +1 more source

Structure-guided decoupled contrastive framework for partial multi-view incomplete multi-label classification

Journal of King Saud University: Computer and Information Sciences
Recently, 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, Tao Zhuang, Xing Jin, Tianyang Cao, Xiyin Wu   +4 more
doaj   +1 more source

Twin Contrastive Learning for Multi-View Clustering

IEEE Access
Multi-view Clustering (MVC) utilizes the complementary and consistent information between multiple views or modal data to more comprehensively reveal the inherent structure and patterns of data. However, mining the invariance and complementarity of multi-
Ansi Zhang, Yang Zheng, Xiaohua Wang, Jie Hu   +3 more
doaj   +1 more source

Self-paced Multi-view Learning for CT-based severity assessment of COVID-19. [PDF]

Biomed Signal Process Control, 2023
Liu Y, Chen B, Zhang Z, Yu H, Ru S, Chen X, Lu G.   +6 more
europepmc   +1 more source

Incomplete multi-view partial multi-label classification via deep semantic structure preservation

Complex & Intelligent Systems
Recent 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, Xiyin Wu, Pai Peng, Zhuhong Zhang, Xiaohuan Lu   +4 more
doaj   +1 more source

scAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data. [PDF]

Bioinformatics, 2023
Zeng P, Ma Y, Lin Z.
europepmc   +1 more source

Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning. [PDF]

Gut Microbes, 2022
Chen Y, Wang H, Lu W, Wu T, Yuan W, Zhu J, Lee YK, Zhao J, Zhang H, Chen W.   +9 more
europepmc   +1 more source