Distributed representations of words are attractive since they provide a means for measuring word similarity. However, most approaches to learning distributed representations are ...
We propose an image hashing algorithm that is based on distributed compression principles. The algorithm assumes the availability of a robust feature vector extracted from the ima...
This paper proposes selective update and cooperation strategies for parameter estimation in distributed adaptive sensor networks. A setmembership filtering approach is employed t...
Stefan Werner, Yih-Fang Huang, Marcello L. R. de C...
We propose a model for the density of cross-spectral coefficients using Normal Variance Mean Mixtures. We show that this model density generalizes the corresponding marginal dens...
Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delg...
Abstract. For large distributed systems built from inexpensive components, one expects to see incessant failures. This paper proposes two models for such faults and analyzes two we...