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. By avoiding explicit principal component analysis (PCA), our algorithm is the first with no runtime dependen...

Articulated models are commonly used for recognition tasks in robotics and in gait analysis, but can also be extremely useful to develop analytical methods targeting spinal deformities studies. The threedimensional analysis of these deformities is critical since they are complex and not restricted to a given plane. Thus, they cannot be assessed as a two-dimensional phenomenon. However, analyzin...

This paper may be regarded as a new numerical method for the analysis of triangular thin plates using the natural area coordinates. Previous studies on the solution of triangular plates with different boundary conditions are mostly based on the Rayleigh-Ritz principle which is performed in the Cartesian coordinates. Consequently, manipulation of the geometry and numerical calculation of the int...

OBJECTIVE Moxibustion is an important traditional Chinese medicine therapy using heat from ignited moxa floss for disease treatment. The purpose of the present study is to establish a reproducible method to assess the color of moxa floss, discriminate the samples based on chromatic coordinates and explore the relationship between chromatic coordinates and total flavonoid content (TFC). METHOD...

q-mode hierarchical cluster (hca) and principal component analysis (pca) were simultaneously applied to groundwater hydrochemical data from the three times in 2004: june, september, and december, along the ain azel aquifer, algeria, to extract principal factors corresponding to the different sources of variation in the hydrochemistry, with the objective of defining the main controls on the h...

targeted extension for heterogeneous farming systems is a challenge in developing countries. farm type identification and characterization based on estimates of income from different farm components allows simplifying diversity in farming systems. use of multivariate statistical techniques, such as principal component analysis (pca) and cluster analysis (ca), help in such farm typology delineat...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...