Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
Source separation techniques like independent component analysis and the more recent non-negative matrix factorization are gaining widespread use for the monaural separation of in...
The object of this paper is to appreciate the computational limits inherent in the combinatorics of an applied concurrent (aka agent-based) language . That language is primarily m...
Pierre-Louis Curien, Vincent Danos, Jean Krivine, ...
Independent Component Analysis is becoming a popular exploratory method for analysing complex data such as that from FMRI experiments. The application of such `model-free' me...
Dependable software systems are difficult to develop because developers must understand and address several interdependent and pervasive dependability concerns. Features that addr...