We propose a new method for the blind separation of multiple binary signals from a single general nonlinear mixture. In addition to the usual independence assumption on the input ...
Konstantinos I. Diamantaras, Theophilos Papadimitr...
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
To specify a Bayes net (BN), a conditional probability table (CPT), often of an effect conditioned on its n causes, needs assessed for each node. Its complexity is generally expon...
In a previous work, the authors have introduced a Mixture of Laplacians model in order to cluster the observed data into the sound sources that exist in an underdetermined two-sens...
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...