An approach is presented for imposing generic hard constraints on deformable models at a low computational cost, while preserving the good convergence properties of snake-like mod...
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...
Column generation algorithms have been specially designed for solving mathematical programs with a huge number of variables. Unfortunately, this method suffers from slow convergen...
Compressive sampling (CS) aims at acquiring a signal at a sampling rate that is significantly below the Nyquist rate. Its main idea is that a signal can be decoded from incomplet...
Biological images have the potential to reveal complex signatures that may not be amenable to morphological modeling in terms of shape, location, texture, and color. An effective ...