The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Abstract. We study the problem of multimodal dimensionality reduction assuming that data samples can be missing at training time, and not all data modalities may be present at appl...
This paper studies the issue of space coordinate change in genetic algorithms, based on two methods: convex quadratic approximations, and principal component analysis. In both met...
Elizabeth F. Wanner, Eduardo G. Carrano, Ricardo H...
We investigate the impact of using non-ideal lowpass filters in the modulated wideband (MWC) converter, which is a recent subNyquist sampling system for sparse wideband analog si...
Yilun Chen, Moshe Mishali, Yonina C. Eldar, Alfred...
We propose a novel algorithm for sparse system identification in the frequency domain. Key to our result is the observation that the Fourier transform of the sparse impulse respo...