This paper is concerned with the estimation of the directionsof-arrival (DOA) of narrowband sources using a sparse spatial spectral model, when the model itself is not precise. Wh...
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Virtual reality based surgical simulators offer the possibility to provide training on a wide range of findings of different pathologies. Current research aims at a high fidelity h...
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Among the many methods for modeling cortical interactions using EEG and MEG data, Multivariate Autoregressive(MVAR) functional connectivity measures have the advantage of providin...