Some neurons in the nucleus HVc of the songbird respond vigorously to sequences of syllables as they appear in the bird's own song (such as AB), but they respond weakly or no...
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Three versions of a novel adaptive channel estimation approach, exploiting the over-sampled complex exponential basis expansion model (CE-BEM), is presented fordoubly selectivechan...
The representation model that considers an image as a sparse linear combination of few atoms of a predefined or learned dictionary has received considerable attention in recent ye...