We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
—Interactions between transcription factors (TFs) are necessary for deciphering the complex mechanisms of transcription regulation in eukaryotes. In this paper, we proposed a nov...
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
In recent years, approaches to control performance and resource optimization for embedded control systems have been receiving increased attention. Most of them focus on theory, whe...
Ricardo Marau, Pedro Leite, Manel Velasco, Pau Mar...
In music genre classification the decision time is typically of the order of several seconds, however, most automatic music genre classification systems focus on short time feat...