Independent Component Analysis, a computationally efficient statistical signal processing technique, has been an area of interest for researchers for many practical applications in...
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
This discussion presents a new perspective of subspace independent component analysis (ICA). The notion of a function of cumulants (kurtosis) is generalized to vector kurtosis. Th...
— We show that independent component analysis (ICA) can be used to find distributed representations for words that can be further processed by thresholding to produce sparse rep...
Skew detection via principal components is proposed as an e ective methodforimageswhich contain other parts than text. It is shown that the negative of the image leads to much mor...