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 ...
"The focus of this book is on spectral modeling applied to audio signals. Spectral modeling has two main components: analysis and synthesis. We analyze sound in terms of spect...
The privacy concerns associated with data analysis over social networks have spurred recent research on privacypreserving social network analysis, particularly on privacypreservin...
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
Spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. ...