Results 161 to 170 of about 82,948 (222)

Unrolling Nonnegative Matrix Factorization With Group Sparsity for Blind Hyperspectral Unmixing

IEEE Transactions on Geoscience and Remote Sensing, 2023
Deep neural networks have shown huge potential in hyperspectral unmixing (HU). However, the large function space increases the difficulty of obtaining the optimal solution with limited unmixing data.
Chunyang Cui, Xinyu Wang, Shaoyu Wang, L. Zhang, Yanfei Zhong   +4 more
semanticscholar   +1 more source

Comprehensive Multiview Representation Learning via Deep Autoencoder-Like Nonnegative Matrix Factorization

IEEE Transactions on Neural Networks and Learning Systems, 2023
Learning a comprehensive representation from multiview data is crucial in many real-world applications. Multiview representation learning (MRL) based on nonnegative matrix factorization (NMF) has been widely adopted by projecting high-dimensional space ...
Haonan Huang, Guoxu Zhou, Qianchuan Zhao, Lifang He, Shengli Xie   +4 more
semanticscholar   +1 more source

Unilateral Orthogonal Nonnegative Matrix Factorization

SIAM Journal on Control and Optimization, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shang, Jun, Chen, Tongwen
openaire   +2 more sources

Community Detection via Multihop Nonnegative Matrix Factorization

IEEE Transactions on Neural Networks and Learning Systems, 2023
Community detection aims at finding all densely connected communities in a network, which serves as a fundamental graph tool for many applications, such as identification of protein functional modules, image segmentation, social circle discovery, to name
Jiewen Guan, Bilian Chen, Xinfeng Huang
semanticscholar   +1 more source

Quadratic nonnegative matrix factorization

Pattern Recognition, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yang, Zhirong, Oja, Erkki
openaire   +5 more sources

Symmetric Nonnegative Matrix Factorization-Based Community Detection Models and Their Convergence Analysis

IEEE Transactions on Neural Networks and Learning Systems, 2021
Community detection is a popular yet thorny issue in social network analysis. A symmetric and nonnegative matrix factorization (SNMF) model based on a nonnegative multiplicative update (NMU) scheme is frequently adopted to address it.
Xin Luo, Zhigang Liu, Long Jin, Yue Zhou, Mengchu Zhou   +4 more
semanticscholar   +1 more source

Convolutive Transfer Function-Based Multichannel Nonnegative Matrix Factorization for Overdetermined Blind Source Separation

IEEE/ACM Transactions on Audio Speech and Language Processing, 2022
Most multichannel blind source separation (BSS) approaches rely on a spatial model to encode the transfer functions from sources to microphones and a source model to encode the source power spectral density.
Taihui Wang, Feiran Yang, Jun Yang
semanticscholar   +1 more source

Spectral-Spatial Hyperspectral Unmixing Using Nonnegative Matrix Factorization

IEEE Transactions on Geoscience and Remote Sensing, 2021
Remotely sensed hyperspectral images contain several bands (at about adjoining frequencies) for a similar zone on the surface of the Earth. Hyperspectral unmixing is a significant method for breaking down hyperspectral images into the components ...
Shaoquan Zhang, Guorong Zhang, Fan Li, Chengzhi Deng, Shengqian Wang, A. Plaza, Jun Li   +6 more
semanticscholar   +1 more source

Factor-Bounded Nonnegative Matrix Factorization

ACM Transactions on Knowledge Discovery from Data, 2021
Nonnegative Matrix Factorization (NMF) is broadly used to determine class membership in a variety of clustering applications. From movie recommendations and image clustering to visual feature extractions, NMF has applications to solve a large number of knowledge discovery and data mining problems.
Kai Liu, Xiangyu Li, Zhihui Zhu, Lodewijk Brand, Hua Wang   +4 more
openaire   +1 more source

Recommender Systems Based on Nonnegative Matrix Factorization: A Survey

IEEE Transactions on Artificial Intelligence
Recommender systems (RSs) have gained significant attention for their ability to model user preferences and predict future trends. Collaborative filtering (CF), particularly through nonnegative matrix factorization (NMF), is a popular method for building
S. Ahmadian, K. Berahmand, M. Rostami, Saman Forouzandeh, Parham Moradi, Mahdi Jalili   +5 more
semanticscholar   +1 more source