Results 41 to 50 of about 1,727,048 (195)

A differentially private nonnegative matrix factorization for recommender system

, 2022
Nonnegative matrix factorization (NMF)-based models have been proven to be highly effective and scalable in addressing collaborative filtering (CF) problems in the recommender system (RS).
Ran, Xun, Ma, Jun, Wang, Yong, Zhang, Leo Yu, Jun Ma, Xun Ran, Yong Wang, Leo Yu Zhang   +7 more
core   +1 more source

Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization

Big Data Mining and Analytics
Nonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. It has been widely used and studied in the multi-view clustering tasks because of its effectiveness.
Guosheng Cui, Ye Li, Jianzhong Li, Jianping Fan   +3 more
doaj   +1 more source

On restricted nonnegative matrix factorization [PDF]

, 2016
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matrix M into a product of a nonnegative n × d matrix W and a nonnegative d × m matrix H. Restricted NMF requires in addition that the column spaces of M and W
Kiefer, Stefan, Marusic, Ines, Worrell, James, Kiefer, S., Shirmohammadi, M., Marusic, I., Shirmohammadi, Mahsa, Worrell, J., Chistikov, D., Chistikov, Dmitry   +9 more
core   +2 more sources

Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection

Complexity, 2019
Nonnegative Matrix Factorization (NMF) is a significant big data analysis technique. However, standard NMF regularized by simple graph does not have discriminative function, and traditional graph models cannot accurately reflect the problem of ...
Yong-Jing Hao, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, Jin-Xing Liu   +4 more
doaj   +1 more source

Plasma Proteomics Identifies Molecular Signatures and Biomarkers Associated With High Structural Damage in Ankylosing Spondylitis

Arthritis &Rheumatology, EarlyView.
Objective Pathologic bone formation in ankylosing spondylitis (AS) is not fully reflected by systemic inflammation, limiting the utility of markers of inflammation for structural damage assessment. This study aimed to identify plasma protein signatures associated with structural damage severity in AS.
Tiantian Sun, Wanlin Liu, Kun Yang, Xiaohan Xu, Yu Wang, Xinning Qu, Yifan Gong, Wenya Zhang, Jie Ma, Hongxiao Liu   +9 more
wiley   +1 more source

NIMFA: A Python Library for Nonnegative Matrix Factorization [PDF]

, 2012
NIMFA is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring.
Zupan, Blaz, Zitnik, Marinka
core   +1 more source

When Collaboration Bridges or Breaks: A Systematic Review of Emerging Trends in Supply Chain Resilience and Sustainability

Business Strategy and the Environment, EarlyView.
ABSTRACT Widespread digital adoption has challenged our understanding of how these tools reshape collaboration, trust and sustainability outcomes across different institutional and network contexts. As networks now pursue resilience and sustainable development in parallel, we map emerging research directions and identify how collaboration and ...
Ari Carisza Graha Prasetia, Luca Urciuoli   +1 more
wiley   +1 more source

Improved Graph-Regularized Discriminative Nonnegative Matrix Factorization for Semi-Supervised Clustering

IEEE Access
Nonnegative matrix factorization (NMF) is an effective dimensionality reduction and representation learning technique that captures the intrinsic structure of nonnegative data by learning low-dimensional, parts-based representations.
Xuzhu Shen, Jie Li
doaj   +1 more source

Blind Source Separation via Time‐Frequency Localization on Sound Spectrogram for Environmental Sound Source Attribution

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT As urban sound environments grow more complex, environmental monitoring increasingly demands not just sound‐level measurement but also source attribution. Current source recognition techniques can identify which sources are present in a mixture, but cannot measure each source's energy contribution, making accountability impossible.
Rui Hu, Zhihao Wu, Yuxin Lin, Yong Xu
wiley   +1 more source

Projective robust nonnegative factorization

, 2016
Nonnegative matrix factorization (NMF) has been successfully used in many fields as a low-dimensional representation method. Projective nonnegative matrix factorization (PNMF) is a variant of NMF that was proposed to learn a subspace for feature ...
You, Jane, Xu, Yong, Lu, Yuwu, Li, Xuelong, Lai, Zhihui, Yuan, Chun   +5 more
core   +1 more source