The canonical problem of solving a system of linear equations arises in numerous contexts in information theory, communication theory, and related fields. In this contribution, we...
Ori Shental, Danny Bickson, Paul H. Siegel, Jack K...
This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. T...
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...