We propose low-rank representation (LRR) to segment data drawn from a union of multiple linear (or affine) subspaces. Given a set of data vectors, LRR seeks the lowestrank represe...
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm b...
: - This paper addresses an inverse controller design for excitation system with changing parameters and nonsmooth nonlinearities in the actuator. The existence of such nonlinearit...
Ontology construction requires an understanding of the meaning and usage of its encoded concepts. While definitions found in dictionaries or glossaries may be adequate for many co...