Results 81 to 90 of about 541,400 (289)

A Multi-View Co-Training Clustering Algorithm Based on Global and Local Structure Preserving

IEEE Access, 2021
Multi-view clustering which integrates the complementary information from different views for better clustering, is a fundamental and important topic in machine learning.
Weiling Cai, Honghan Zhou, Le Xu
doaj   +1 more source

Uncoupling Type I Interferon Benefits From Inflammatory Toxicity: Transformer‐Prioritized Precision Agonists for Potent and Safer Cancer Immunotherapy

Advanced Science, EarlyView.
A Transformer‐based AI framework, DLINP, screens millions of compounds to identify Co68, a cobalt‐pincer organometallic complex that biases TLR4‐MD2 signaling toward antitumor interferon activation while suppressing inflammatory toxicity through an early TLR4‐SYK‐STAT1 axis.
Xuefei Guo, Yang Zhao, Xianle Rong, Xingyu Chen, Xiao Wang, Tianyi Liu, Yunfei Xie, Yushu Zou, Pingsen Zhao, Qiang Liu, Fuping You   +10 more
wiley   +1 more source

Robust multiview subspace clustering method based on multi-kernel low-redundancy representation learning

Tongxin xuebao, 2021
Considering the impact of high dimensional data redundancy and noise interference on multiview subspace clustering, a robust multiview subspace clustering method based on multi-kernel low redundancy representation learning was proposed.Firstly, by ...
Ao LI, Zhuo WANG, Xiaoyang YU, Deyun CHEN, Yingtao ZHANG, Guanglu SUN   +5 more
doaj   +2 more sources

Convolutional Subspace Clustering Network With Block Diagonal Prior

IEEE Access, 2020
Standard methods of subspace clustering are based on self-expressiveness in the original data space, which states that a data point in a subspace can be expressed as a linear combination of other points. However, the real data in raw form are usually not
Junjian Zhang, Chun-Guang Li, Tianming Du, Honggang Zhang, Jun Guo   +4 more
doaj   +1 more source

Subspace Clustering by Capped l(1) Norm

, 2016
Subspace clustering, as an important clustering problem, has drawn much attention in recent years. State-of-the-art methods generally try to design an efficient model to regularize the coefficient matrix while ignore the influence of the noise model on
Tao, Dacheng, Quanmao Lu, Yongsheng Dong, Dacheng Tao, Lu, Quanmao, Li, Xuelong, Dong, Yongsheng, Dong, YS (reprint author), Xuelong Li   +8 more
core   +1 more source

Subspace clustering using ensembles of K-subspaces

Information and Inference: A Journal of the IMA, 2020
Abstract Subspace clustering is the unsupervised grouping of points lying near a union of low-dimensional linear subspaces. Algorithms based directly on geometric properties of such data tend to either provide poor empirical performance, lack theoretical guarantees or depend heavily on their initialization.
Lipor, John, Hong, David, Tan, Yan Shuo, Balzano, Laura   +3 more
openaire   +2 more sources

Brain Network Dynamics of Local and Global Predictive Processing in Aging

Advanced Science, EarlyView.
Separation of concurrent whole‐brain networks in source‐reconstructed magnetoencephalography (MEG) data suggests that healthy aging reorganizes, rather than uniformly attenuates, neural responses elicited from hierarchical auditory violations. Enhanced early sensory deviance processing alongside reduced higher‐order cognitive responses suggests a large‐
Mathias Houe Andersen, Gemma Fernández‐Rubio, David R. Quiroga‐Martinez, Mattia Rosso, Mathias Klarlund, Kit Melissa Larsen, Hartwig Roman Siebner, Morten L. Kringelbach, Peter Vuust, Leonardo Bonetti   +9 more
wiley   +1 more source

Partial Multi-view Subspace Clustering

, 2018
For many real-world multimedia applications, data are often described by multiple views. Therefore, multi-view learning researches are of great significance. Traditional multi-view clustering methods assume that each view has complete data.
Luo, Xiangyang, Zheng, Xin, Xu, Nan, Guo, Yanqing, Wang, Qianyu   +4 more
core   +1 more source

Adaptive Graph Convolutional Subspace Clustering [PDF]

, 2023
Spectral-type subspace clustering algorithms have shown excellent performance in many subspace clustering applications. The existing spectral-type subspace clustering algorithms either focus on designing constraints for the reconstruction coefficient ...
Wei, Lai, Chen, Zhengwei, Yin, Jun, Zhou, Rigui, Liu, Jin, Zhu, Changming   +5 more
core  

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source