In this paper we introduce a new embedding technique to find the linear projection that best projects labeled data samples into a new space where the performance of a Nearest Neig...
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
This paper focuses on audio-visual (using facial expression, shoulder and audio cues) classification of spontaneous affect, utilising generative models for classification (i) in t...
Abstract. Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regres...