A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Recently, sparse coding has been receiving much attention in object and scene recognition tasks because of its superiority in learning an effective codebook over k-means clusterin...
The paper presents a voice conversion framework that can be used in real-time applications. The conversion technique is based on hybrid (deterministic/stochastic) parametric speec...
In this paper we present a method which allows the statistical analysis of nanoelectronic Boolean networks with respect to timing uncertainty and noise. All signals are considered...
Oliver Soffke, Peter Zipf, Tudor Murgan, Manfred G...
We propose a method based on sparse representation
(SR) to cluster data drawn from multiple low-dimensional
linear or affine subspaces embedded in a high-dimensional
space. Our ...