ABSTRACT. Upon the discovery of power laws [8, 16, 30], a large body of work in complex network analysis has focused on developing generative models of graphs which mimick real-wor...
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
In this paper, we consider the problem of choosing disks (that we can think of as corresponding to wireless sensors) so that given a set of input points in the plane, there exists ...
Matt Gibson, Gaurav Kanade, Kasturi R. Varadarajan
We study the complexity of computing the real solutions of a bivariate polynomial system using the recently proposed algorithm Bisolve [3]. Bisolve is a classical elimination metho...
Abstract—We consider a certain class of large random matrices, composed of independent column vectors with zero mean and different covariance matrices, and derive asymptotically ...
Compressive sensing (CS) exploits the sparsity present in many common signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, ...
Mark A. Davenport, Jason N. Laska, John R. Treichl...
We present an algorithm for computing Fp, the pth moment of an n-dimensional frequency vector of a data stream, for p > 2, to within 1 ± factors, ∈ (0, 1] with high constant...
— Mobile ad hoc networks (MANETs) are dynamic wireless networks without any infrastructure. These networks are weak against many types of attacks. One of these attacks is the bla...
H. A. Esmaili, M. R. Khalili Shoja, Hossein Gharae...
In the algebraic theory of codes and formal languages, the set Q of all primitive words over some alphabet Σ has received special interest. With this survey article we give an ove...