Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
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...
Analyzing accidents is a vital exercise in the development of safety-critical software systems to prevent past accidents from reoccurring in the future. Current practices such as ...
Tariq Mahmood, Edmund Kazmierczak, Tim Kelly, Denn...
Distance-preserving projection based perturbation has gained much attention in privacy-preserving data mining in recent years since it mitigates the privacy/accuracy tradeoff by ac...
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...