We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
We apply the concept of network-consciousness to image compression, an approach that does not simply optimize compression, but which optimizes overall performance when compressed i...
The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors independently distributed...
Animashree Anandkumar, Joseph E. Yukich, Lang Tong...
— MPSoC is evolving towards processor-pool (PP)-based architectures, which employ hierarchical on-chip network for inter- and intra-PP communication. Since the design space of PP...
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...