In the STS-based mapping, we are requested to obtain the correct order of probes in a DNA sequence from a given set of fragments or equivalently a hybridization matrix A. It is wel...
: The initialisation of a neural network implementation of Sammon's mapping, either randomly or based on the principal components (PCs) of the sample covariance matrix, is exp...
Boaz Lerner, Hugo Guterman, Mayer Aladjem, Its'hak...
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Abstract— In this paper, the Independence Relative Map algorithm is presented. The algorithm aims to achieve the independence of relative map states. We show that using dependent...
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...