Abstract In this paper we propose a reduced-reference quality assessment algorithm which computes an approximation of the Structural SIMilarity (SSIM) metrics exploiting coding too...
Marco Tagliasacchi, Giuseppe Valenzise, Matteo Nac...
— Recent work has revealed a close connection between certain information theoretic divergence measures and properties of Mercer kernel feature spaces. Specifically, it has been...
This paper discusses a new type of semi-supervised document clustering that uses partial supervision to partition a large set of documents. Most clustering methods organizes docum...
Computing a suitable measure of consensus among several clusterings on the same data is an important problem that arises in several areas such as computational biology and data mi...
Piotr Berman, Bhaskar DasGupta, Ming-Yang Kao, Jie...
Clustering is a prominent method in the data mining field. It is a discovery process that groups data such that intra cluster similarity is maximized and the inter cluster similar...