Abstract. There exist numerous algorithms that cluster data-points from largescale genomic experiments such as sequencing, gene-expression and proteomics. Such algorithms may emplo...
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
In this paper, we first develop a direct Bayesian based Support Vector Machine by combining the Bayesian analysis with the SVM. Unlike traditional SVM-based face recognition metho...
System identification is an abductive task which is affected by several kinds of modeling assumptions and measurement errors. Therefore, instead of optimizing values of parameters ...
We propose two methods to passively measure and monitor changes in round-trip times (RTTs) throughout the lifetime of a TCP connection. Our first method associates data segments w...