A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a m...
Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Least-squares estimation has always been the main approach when applying prediction error methods (PEM) in the identification of linear dynamical systems. Regardless of the estim...
Abstract The ability of the modern graphics processors to operate on large matrices in parallel can be exploited for solving constrained image deblurring problems in a short time. ...
Valeria Ruggiero, Thomas Serafini, Riccardo Zanell...
We describe our experiments with training algorithms for tree-to-tree synchronous tree-substitution grammar (STSG) for monolingual translation tasks such as sentence compression a...