Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
For regular, sparse, linear systems, like those derived from regular grids, using High Performance Fortran (HPF) for iterative solvers is straightforward. However, for irregular ma...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...