Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
In this paper we present a novel approach for estimating featurespace maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maxim...
Arnab Ghoshal, Daniel Povey, Mohit Agarwal, Pinar ...
In recent years, Support Vector Machines (SVMs) were successfully applied to a wide range of applications. Their good performance is achieved by an implicit non-linear transformat...
David Martens, Bart Baesens, Tony Van Gestel, Jan ...
Various types of moments have been used to recognize image patterns in a number of applications. However, only few works have paid attention to the completeness property of the in...
Abstract. This paper presents a fast algorithm for robust registration of shapes implicitly represented by signed distance functions(SDF). The proposed algorithm aims to recover th...
Muayed S. Al-Huseiny, Sasan Mahmoodi, Mark S. Nixo...