The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Parallel programming continues to be difficult, despite substantial and ongoing research aimed at making it tractable. Especially dismaying is the gulf between theory and the pract...
In this paper we present a general domain for the analysis of workflows and workflow components based on the notion of a collection of Turing machines sharing a set of tapes. We s...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...