We investigate the robust PCA problem of decomposing an observed matrix intothe sum of a low-rank and a sparse error matrices via convex programming PrincipalComponent Pursuit (PCP). In contrast to previous studies that assume the supportof the sparse error matrix is generated by uniform Bernoulli sampling, we allow non-uniform sampling, i.e., entries of the low-rank matrix are ...

Keratinophilic fungi are natural colonizers of keratinic substrates. Some are keratinolytic and play an important ecological role in decomposing α-keratins, the insoluble fibrous proteins. Because of the tight packing of their polypeptide chains in α-helix structures and their linkage by disulphide bridges, they are poorly biodegradable. Two main forms of attack have been identified: surface er...

In this paper we propose a novel approach for image encryption supported by lossy compression using multilevel wavelet transform. We first decompose the input image using multilevel 2-D wavelet transform, and thresholding is applied on the decomposed structure to get compressed image. Then we carry out encryption by decomposing the compressed image by multi-level 2-D Haar Wavelet Transform at t...

Mammography is the most efficient method for breast cancer early detection. Clusters of microcalcifications are the sign of breast cancer and their early detection is the key to improve breast cancer prognosis. Microcalcifications appear in mammogram as tiny granular points, which are difficult to observe by radiologists due to their small size. An efficient method for automatic and accurate de...

In this paper we present a unified approach of decomposing the fundamental and the essential matrix using information about epipoles. In contrast to other methods our approach is based on Householder transformations and can deal with finite and infinite epipoles. Our decomposition is able to yield a minimal parametrization of the fundamental and the essential matrix and retains their characteri...

Many social phenomena involve a set of dyadic relations among agents whose actions may be dependent. Although individualistic approaches have frequently been applied to analyze social processes, these are not generally concerned with dyadic relations, nor do they deal with dependency. This article describes a mathematical procedure for analyzing dyadic interactions in a social system. The propo...

In this paper, we improve the efficiency of kernelized support vector machine (SVM) for image classification using linearized kernel data representation. Inspired by Nyström approximation, we propose a decomposition technique for converting the kernel data matrix into an approximated primal form. This allows us to apply the approximated kernelized data in the primal form of linear SVMs, and ach...

PURPOSE AND METHODS This paper examines the social cognitive processes that regulate people's eating behavior. Specifically, we examine how eating behavior can be regulated by reflective, deliberative processes as well as automatic and habitual processes. Moreover, we consider how these processes operate when people are not only initiating a change in behavior but also maintaining the behavior ...