Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Modularization is a well-known concept to structure software systems as well as their specifications. Modules are equipped with export and import interfaces and thus can be connec...
We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
Abstract This paper addresses the problem of moving object reconstruction. Several methods have been published in the past 20 years including stereo reconstruction as well as multi...
The major concerns in state-of-the-art model reduction algorithms are: achieving accurate models of sufficiently small size, numerically stable and efficient generation of the mod...
Joel R. Phillips, Luca Daniel, Luis Miguel Silveir...