Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Abstract. We present a new “lifting” approach for the solution of nonlinear optimization problems (NLPs) that have objective and constraint functions with intermediate variable...
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
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 ...
Segmentation of speech signals is a crucial task in many types of speech analysis. We present a novel approach at segmentation on a syllable level, using a Bidirectional Long-Shor...
Christian Landsiedel, Jens Edlund, Florian Eyben, ...