—A unified analytical framework for optimum power allocation in the unordered V-BLAST algorithm and its comparative performance analysis are presented. Compact closed-form appro...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
—This paper describes new algorithms for throughput optimization in a mobile backbone network. This hierarchical communication framework combines mobile backbone nodes, which hav...
Abstract--Assuming that evolutionary multiobjective optimization (EMO) mainly deals with set problems, one can identify three core questions in this area of research: (i) how to fo...
Background: Phylogenetic analysis is emerging as one of the most informative computational methods for the annotation of genes and identification of evolutionary modules of functi...