Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
World Wide Web (WWW) is a vast source of information, the problem of information overload is more acute than ever. Due to noise in WWW, it is becoming hard to find usable informati...
Typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may ...
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Using multiple independent networks (also known as rails) is an emerging technique to overcome bandwidth limitations and enhance fault tolerance of current high-performance parall...
Salvador Coll, Eitan Frachtenberg, Fabrizio Petrin...