In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
An increasing number of comfortable publishing systems nowadays leads to documents containing more than just textual information. Graphics and images are combined with text and of...
—This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing...
This paper presents a new algorithm based on shift-invariant probabilistic latent component analysis that analyzes harmonic structures in an audio signal. Each note in a constant-...
Feature modeling is commonly used to capture the commonalities and variabilities of systems in a domain during Domain Analysis. The output of feature modeling will be some reusabl...
Fei Cao, Barrett R. Bryant, Carol C. Burt, Zhishen...