Results 101 to 110 of about 465,256 (146)
On the Eigenspectrum of the Gram matrix and the generalisation error of kernel PCA
In this paper we analyze the relationships between the eigenvalues of the m x m Gram matrix K for a kernel k(.,.) corresponding to a sample x1,...,xm drawn from a density p(x) and the eigenvalues of the corresponding continuous eigenproblem. We bound the
Shawe-Taylor, John +3 more
core +1 more source
A Modified Adaptive PCA Learning based Method for Image Denoising
G. M. Shaker, A. Hefnawy, M. Dessouky
semanticscholar +1 more source
Degradation of p-chloroaniline (PCA) in packed-bed bioreactor
With p-chloroaniline (PCA) as a selected substrate, the mixed microorganisms assimilating it as the sole source of carbon and nitrogen were obtained by acclimation technique from the enriched cultural products of degraded p-dichlorobenzen (p-DCB).
Inst. Hydrobiol., Acad. Sinica, Wuhan 430072, China +4 more
core
An p theory of PCA and spectral clustering
Principal Component Analysis (PCA) is a powerful tool in statistics and machine learning. While existing study of PCA focuses on the recovery of principal components and their associated eigenvalues, there are few precise characterizations of individual ...
Wang, Kaizheng +2 more
core +1 more source
Principal Component Analysis (PCA) is a widely used tool for dimensional reduction and data visualization. However, it cannot be used directly for microbiome data.
Huang, Tianshu Jr
core
Monitoring based on MIC-PCA and SVDD for industrial process
Complex industrial processes are often non-linear and non-Gaussian, while the traditional principal component analysis (PCA) method assumes that the data are Gaussian and linear.
Wang ZW(王中伟) +3 more
core
PCA loadings for the first two axes of the best PCA model (PCA 3).
PCA loadings for the first two axes of the best PCA model (PCA 3).
Esteban Pinto (8635875) +3 more
core +1 more source
L. Callister, A. Henning and P. Golsby-Smith, 1986
Lee Callister (centre) winner of the PCA/AIP Award is congratulated by Adrian Henning, National President of AIP (left) and Peter Golsby-Smith of PCA (right).
Swinburne Institute of Technology
core
Graph PCA Hashing for Similarity Search
Xiaofeng Zhu +5 more
semanticscholar +1 more source
Geodesic PCA in the Wasserstein space by Convex PCA
Jérémie Bigot +3 more
semanticscholar +1 more source

