Results 51 to 60 of about 1,698,574 (297)

Discriminant projective non-negative matrix factorization. [PDF]

PLoS ONE, 2013
Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W(T) X as their coefficients, i.e., X≈WW(T) X.
Naiyang Guan, Xiang Zhang, Zhigang Luo, Dacheng Tao, Xuejun Yang   +4 more
doaj   +1 more source

Simplicial nonnegative matrix factorization

The 2013 RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF), 2013
Nonnegative matrix factorization (NMF) plays a crucial role in machine learning and data mining, especially for dimension reduction and component analysis. It is employed widely in different fields such as information retrieval, image processing, etc. After a decade of fast development, severe limitations still remained in NMFs methods including high ...
Duy Khuong Nguyen, Khoat Than, Tu Bao Ho
openaire   +2 more sources

Heuristics for exact nonnegative matrix factorization [PDF]

Journal of Global Optimization, 2015
32 pages, 2 figures, 16 ...
Arnaud Vandaele, Nicolas Gillis, François Glineur, Daniel Tuyttens   +3 more
openaire   +7 more sources

Early Spatial and Contextual Coding Deficits in Hippocampal CA1 Precede Performance Decline in an Alzheimer's Disease Model

Advanced Science, EarlyView.
Two‐photon calcium imaging in behaving 5xFAD mice reveals early CA1 coding deficits before behavioral decline. Task‐related place cell activity and splitter cell trajectory coding are impaired, with reduced retrospective dominance and greater prospective weighting.
Yimei Li, Mary Ann Go, Hualong Zhang, Robertas Aleksynas, Juliana Kim, Mingyang Gao, Seigfred Prado, Magdalena Sastre, Simon R. Schultz   +8 more
wiley   +1 more source

Dynamics of products of nonnegative matrices

Extracta Mathematicae, 2022
The aim of this manuscript is to understand the dynamics of products of nonnegative matrices. We extend a well known consequence of the Perron-Frobenius theorem on the periodic points of a nonnegative matrix to products of finitely many nonnegative ...
S. Jayaraman, Y.K. Prajapaty, S. Sridharan   +2 more
doaj  

Monotonous (semi-)nonnegative matrix factorization [PDF]

Proceedings of the Second ACM IKDD Conference on Data Sciences, 2015
Nonnegative matrix factorization (NMF) factorizes a non-negative matrix into product of two non-negative matrices, namely a signal matrix and a mixing matrix. NMF suffers from the scale and ordering ambiguities. Often, the source signals can be monotonous in nature.
Nirav Bhatt, Arun Ayyar
openaire   +3 more sources

Towards a Compositional Framework for Describing Human Phenotypes

Advanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu, Yunchao Ling, Xinyue Hu, Wei Chen, Rong Zhou, Xinhao Zhuang, Yanfeng Jiang, Jialu Zhao, Xingdong Chen, Jingchun Luo, Li Jin, Guoqing Zhang   +11 more
wiley   +1 more source

Integrated Multi‐Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC

Advanced Science, EarlyView.
Coexisting DCIS and IDC samples are profiled using spatial transcriptomics, single‐cell RNA sequencing, and single‐cell DNA sequencing. Integrative multi‐omics analysis reveals distinct malignant epithelial and microenvironmental features between DCIS and IDC, which are further validated using Xenium and multiplex immunohistochemistry.
Ning Zhang, Tong Wan, Siyue Zhang, Yunzhen Jiang, Peng Su, Jixin Liu, Zhitong Chen, Jie Hao, Haoyu Wang, Bing Chen, Wenjing Zhao, Lijuan Wang, Tao Xing, Qihuang Zhang, Ulf Schmitz, Zhiyong Ding, Nicola Crosetto, Bingqiang Liu, Qifeng Yang   +18 more
wiley   +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

Optimization of identifiability for efficient community detection

New Journal of Physics, 2020
Many physical and social systems are best described by networks. And the structural properties of these networks often critically determine the properties and function of the resulting mathematical models.
Hui-Jia Li, Lin Wang, Yan Zhang, Matjaž Perc   +3 more
doaj   +1 more source