A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
Most clustering algorithms operate by optimizing (either implicitly or explicitly) a single measure of cluster solution quality. Such methods may perform well on some data sets bu...
Background: The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultane...
Raja Loganantharaj, Satish Cheepala, John Clifford
A novel center-based clustering algorithm is proposed in this paper. We first formulate clustering as an NP-hard linear integer program and we then use linear programming and the ...
Emergence of the web and online computing applications gave rise to rich large scale social activity data. One of the principal challenges then is to build models and understandin...