For centuries, scholars have explored the deep links among human languages. In this paper, we present a class of probabilistic models that use these links as a form of naturally o...
In this paper, an HMM-embedded unsupervised learning approach is proposed to detect the music events by grouping the similar segments of the music signal. This approach can cluste...
Reducing the number of labeled examples required to learn accurate prediction models is an important problem in structured output prediction. In this paper we propose a new transd...
Abstract. Neurobiological studies showed the important role of Centeral Pattern Generators for spinal cord in the control and sensory feedback of animals' locomotion. In this ...
John Nassour, Patrick Henaff, Fathi Ben Ouezdou, G...
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...