Currently the best algorithms for transcription factor binding site predictions are severely limited in accuracy. However, a non-linear combination of these algorithms could improv...
Mark Robinson, Offer Sharabi, Yi Sun, Rod Adams, R...
Traditional text classification algorithms are based on a basic assumption: the training and test data should hold the same distribution. However, this identical distribution assum...
Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in...
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
This paper addresses the issue of the explanation of the result given to the end-user by a classifier, when it is used as a decision support system. We consider machine learning cl...