The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

A note on maximizing a submodular set function subject to a knapsack constraint -
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We investigate the behavior of quasi-Newton algorithms applied to minimize a nonsmooth
function f, not necessarily convex. We introduce an inexact line search that generates a …

The problem of maximizing the determinant of a matrix subject to linear matrix inequalities
(LMIs) arises in many fields, including computational geometry, statistics, system …

Submodular function maximization is a central problem in combinatorial optimization,
generalizing many important problems including Max Cut in directed/undirected graphs and …

We study spatial sampling design for prediction of stationary isotropic Gaussian processes
with estimated parameters of the covariance function. The key issue is how to incorporate …

Submodular function maximization is a central problem in combinatorial optimization,
generalizing many important problems including Max Cut in directed/undirected graphs and …

Abstract The Karhunen-Loeve Expansion (KL expansion) is a bi-orthogonal stochastic
process expansion. In the field of stochastic process, the Karhunen-Loeve expansion …

To design a transportation sensor network, the decision maker needs to determine what
sensor investments should be made, as well as when, how, where, and with what …

Given a positive semidefinte matrix L whose columns and rows are indexed by a set U, and
a partition matroid M=(U, I), we study the problem of selecting a basis B of M such that the …