Motivated by the slow learning properties of multilayer perceptrons (MLPs) which utilize computationally intensive training algorithms, such as the backpropagation learning algorit...
In this work, we derive an algebraic formulation for the scalar linear network coding problem as an alternative to the one presented by Koetter et al in [1]. Using an equivalence b...
— Anypath routing, a new routing paradigm, has been proposed to improve the performance of wireless networks by exploiting the spatial diversity and broadcast nature of the wirel...
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...
Bipartite network flow problems naturally arise in applications such as selective assembly and preemptive scheduling. This paper presents fast algorithms for these problems that ...