Abstract—The discovery of locally and significantly correlated subpatterns within a two-dimensional dataset has recently become quite popular and is amongst others addressed by ...
Our research aims at building computational models of word meaning that are perceptually grounded. Using computer vision techniques, we build visual and multimodal distributional ...
Elia Bruni, Gemma Boleda, Marco Baroni, Nam-Khanh ...
This paper describes a novel approach to nd a tighter bound of the transformation of the Min-Max problems into the one of Least-Square Estimation. It is well known that the above ...
3D Bayesian regularization applied to diffusion tensor MRI is presented here. The approach uses Markov Random Field ideas and is based upon the definition of a 3D neighborhood syst...
Gaussian mixture models (GMMs) are commonly used to model the spectral distribution of speech signals for text-independent speaker verification. Mean vectors of the GMM, used in c...
Eryu Wang, Kong-Aik Lee, Bin Ma, Haizhou Li, Wu Gu...