Recently, a vector version of Witsenhausen's counterexample was considered and it was shown that in that limit of infinite vector length, certain quantization-based strategie...
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
In a previous paper the authors argued the case for incorporating ideas from innate immunity into artificial immune systems (AISs) and presented an outline for a conceptual framewo...
Abstract. As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application...
Outage probabilities in wireless networks depend on various factors: the node distribution, the MAC scheme, and the models for path loss, fading and transmission success. In prior ...
Riccardo Giacomelli, Radha Krishna Ganti, Martin H...
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sens...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
The ability to detect weak distributed activation patterns in networks is critical to several applications, such as identifying the onset of anomalous activity or incipient conges...
Aarti Singh, Robert D. Nowak, A. Robert Calderbank
traction Problem for PCF Hyland-Ong games model Concrete Representation Compositional Semantics? A Concrete Representation of Observational Equivalence for PCF Martin Churchill, Ji...