Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
We present the Ka-admin project that addresses the problem of collecting, visualizing and feeding back any grid information, trace or snapshot, compliant to an XML-like model. Rea...
mes, abstracts and year of publication of all 853 papers published.1 We then applied Porter stemming and stopword removal to this text, represented terms from the elds with twice t...
Alan F. Smeaton, Gary Keogh, Cathal Gurrin, Kieran...
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...