I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Sparse Matrix-Vector multiplication (SpMV) is a very challenging computational kernel, since its performance depends greatly on both the input matrix and the underlying architectur...
Vasileios Karakasis, Georgios I. Goumas, Nectarios...
Analysis of postgenomic biological data (such as microarray and SNP data) is a subtle art and science, and the statistical methods most commonly utilized sometimes prove inadequat...
Super-resolution algorithms combine multiple low resolution images into a single high resolution image. They have received a lot of attention recently in various application domai...
We consider the problem of sampling piecewise sinusoidal signals. Classical sampling theory does not enable perfect reconstruction of such signals since they are not bandlimited. ...