In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
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 ...
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive perf...
Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovi...
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
Advanced multimedia applications (e.g. based on MPEG-4) will consist of multiple scalable multimedia objects. This scalability enables the application to adapt to different proces...
Nam Pham Ngoc, Gauthier Lafruit, Jean-Yves Mignole...