This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
In this paper we present an algorithm which uses adaptive selection of low-level features for main subject detection. The algorithm first computes low-level features such as contr...
The scope of the well-known k-means algorithm has been
broadly extended with some recent results: first, the k-
means++ initialization method gives some approximation
guarantees...
Following Hartigan (1975), a cluster is defined as a connected component of the t-level set of the underlying density, that is, the set of points for which the density is greater...
We propose a new parallelization scheme for the hmmsearch function of the HMMER software, in order to target FPGA technology. hmmsearch is a very compute intensive software for bio...