Results 81 to 90 of about 2,261,156 (339)

Optimisation of on-line principal component analysis

, 1998
Different techniques, used to optimise on-line principal component analysis, are investigated by methods of statistical mechanics. These include local and global optimisation of node-dependent learning-rates which are shown to be very efficient in ...
Biehl M, Biehl M, Biehl M, Bishop C, D Saad, E Schlösser, Hertz J, Kinouchi O, M Biehl, Rattray M, Saad D, Sanger T   +11 more
core   +2 more sources

On the multiway principal component analysis

The Annals of Statistics
Multiway data are becoming more and more common. While there are many approaches to extending principal component analysis (PCA) from usual data matrices to multiway arrays, their conceptual differences from the usual PCA, and the methodological implications of such differences remain largely unknown.
Ouyang, Jialin, Yuan, Ming
openaire   +3 more sources

Age and Visual Contribution Effects on Postural Control Assessed by Principal Component Analysis of Kinematic Marker Data [PDF]

, 2023
Arunee Promsri
openalex   +1 more source

Hematopoietic (stem) cells—The elixir of life?

FEBS Letters, EarlyView.
The aging of HSCs (hematopoietic stem cells) and the blood system leads to the decline of other organs. Rejuvenating aged HSCs improves the function of the blood system, slowing the aging of the heart, kidney, brain, and liver, and the occurrence of age‐related diseases.
Emilie L. Cerezo, Jonah Anderson, Emilie Dinh Vedrenne, Noël Yeh Martín, Jette Lengefeld   +4 more
wiley   +1 more source

Principal Component Analysis of Weak Lensing Surveys

, 2005
We study degeneracies between cosmological parameters and measurement errors from cosmic shear surveys using a principal component analysis of the Fisher matrix.
Anderson, Bacon, Bacon, Bacon, Bartelmann, Brainerd, Brown, Colless, Contaldi, D. Munshi, Efstathiou, Efstathiou, Groch, Hamilton, Hamilton, Heavens, Hoekstra, Hoekstra, Hu, Hu, Huterer, Huterer, Hämmerle, Ishak, Jarvis, Kaiser, Kaiser, Kaiser, Kilbinger, Kilbinger, Kilbinger, M. Kilbinger, Maoli, Massey, Mastsubara, Mellier, Peacock, Rhodes, Rocha, Réfrégier, Réfrégier, Schneider, Schneider, Schneider, Schneider, Seljak, Spergel, Tegmark, Tegmark, Tereno, van Waerbeke, van Waerbeke, van Waerbeke, Vogeley, Wang, Wittman   +55 more
core   +4 more sources

Structural insights into lacto‐N‐biose I recognition by a family 32 carbohydrate‐binding module from Bifidobacterium bifidum

FEBS Letters, EarlyView.
Bifidobacterium bifidum establishes symbiosis with infants by metabolizing lacto‐N‐biose I (LNB) from human milk oligosaccharides (HMOs). The extracellular multidomain enzyme LnbB drives this process, releasing LNB via its catalytic glycoside hydrolase family 20 (GH20) lacto‐N‐biosidase domain.
Xinzhe Zhang, Naoki Sunagawa, Toma Kashima, Kiyohiko Igarashi, Akimasa Miyanaga, Shinya Fushinobu   +5 more
wiley   +1 more source

Principal Component Projection Without Principal Component Analysis

, 2016
We show how to efficiently project a vector onto the top principal components of a matrix, without explicitly computing these components. Specifically, we introduce an iterative algorithm that provably computes the projection using few calls to any black-box routine for ridge regression.
Frostig, Roy, Musco, Cameron, Musco, Christopher, Sidford, Aaron   +3 more
openaire   +2 more sources

Diagnosis of Dry Eye Disease Using Principal Component Analysis: A Study in Animal Models of the Disease [PDF]

, 2021
Robert Honkanen, Barbara Nemesure, Liqun Huang, Basil Rigas   +3 more
openalex   +1 more source

The zinc finger domains of PARP‐1 are selectively and potently inhibited by the Au(I)‐based drugs sodium aurothiomalate and aurothioglucose

FEBS Letters, EarlyView.
PARP‐1 is a key enzyme in the DNA damage response, and its inhibition induces cancer cell death via synthetic lethality. Au(I)‐based drugs, such as aurothioglucose and sodium aurothiomalate, block PARP‐1's DNA‐dependent activity by targeting its zinc finger domains.
Uliana Bashtanova, Melinda Jane Duer
wiley   +1 more source

Lazy stochastic principal component analysis

, 2017
Stochastic principal component analysis (SPCA) has become a popular dimensionality reduction strategy for large, high-dimensional datasets. We derive a simplified algorithm, called Lazy SPCA, which has reduced computational complexity and is better ...
Li, Li, Nguyen, Dinh, Wojnowicz, Michael, Zhao, Xuan   +3 more
core   +1 more source