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Graph Regularized Non-Negative Low-Rank Matrix Factorization for Image Clustering

open access: yesIEEE Transactions on Cybernetics, 2017
Non-negative matrix factorization (NMF) has been one of the most popular methods for feature learning in the field of machine learning and computer vision.
Xuelong Li   +2 more
exaly   +2 more sources
Some of the next articles are maybe not open access.

Robust Manhattan non-negative matrix factorization for image recovery and representation

Information Sciences, 2020
Xiangguang Dai   +2 more
exaly  

An enhanced EMG-driven Musculoskeletal model based on non-negative matrix factorization

Biomedical Signal Processing and Control, 2023
Jianmin Li, Ruyi Wang, Lizhi Pan
semanticscholar   +1 more source

Semi-supervised multi-view clustering with dual hypergraph regularized partially shared non-negative matrix factorization

Science China Technological Sciences, 2022
Dongping Zhang   +4 more
semanticscholar   +1 more source

Max-margin Non-negative Matrix Factorization

Image and Vision Computing, 2012
B. G. Vijay Kumar   +2 more
openaire   +1 more source

Non-negative matrix factorization with α-divergence

Pattern Recognition Letters, 2008
Andrzej Cichocki   +2 more
exaly  

An Efficient Non-Negative Matrix-Factorization-Based Approach to Collaborative Filtering for Recommender Systems

IEEE Transactions on Industrial Informatics, 2014
Xin Luo, Mengchu Zhou, Yunni Xia
exaly  

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