Results 101 to 110 of about 1,699,128 (261)

Reliable Conflictive Multi-View Learning

Proceedings of the AAAI Conference on Artificial Intelligence
Multi-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, Si, Jiajun, Guan, Ziyu, Zhao, Wei, Wu, Yue, Gao, Xiyue   +5 more
openaire   +2 more sources

Multi-view Graph Clustering Algorithm Based on Dual Contrastive Learning and Hard Sample Mining [PDF]

Jisuanji gongcheng
As 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
doaj   +1 more source

3D (Bio) Printing Combined Fiber Fabrication Methods for Tissue Engineering Applications: Possibilities and Limitations

Advanced Functional Materials, EarlyView.
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana, Indra Apsite, Leonid Ionov   +2 more
wiley   +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

Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications

Advanced Functional Materials, EarlyView.
Quantum emitters in hexagonal boron nitride have emerged as a promising candidate for quantum information science. This review examines the fundamentals of these quantum emitters, including their level structures, defect engineering, and their possible chemical structures.
Thi Ngoc Anh Mai, Md Shakhawath Hossain, Nhat Minh Nguyen, Yongliang Chen, Chaohao Chen, Xiaoxue Xu, Quang Thang Trinh, Toan Dinh, Toan Trong Tran   +8 more
wiley   +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

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

Privacy-Preserving Decentralized Federated Multi-View Clustering [PDF]

Jisuanji gongcheng
In 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
doaj   +1 more source

Synchrotron Radiation for Quantum Technology

Advanced Functional Materials, EarlyView.
Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader, Sakura Pascarelli, Klaus Attenkofer, Anna A. Makarova, Karsten Holldack, Kai Rossnagel, Kristiaan Temst, George Kourousias, Stefano Carretta, Caterina Biscari, Helmut Dosch   +10 more
wiley   +1 more source

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.
doaj   +1 more source