@misc{white_2023, title={Computational Linear Algebra}, ISBN={9781003304128}, url={http://dx.doi.org/10.1201/9781003304128}, DOI={10.1201/9781003304128}, abstractNote={Courses on linear algebra and numerical analysis need each other. Often NA courses have some linear algebra topics, and LA courses mention some topics from numerical analysis/scientific computing. This text merges these two areas into one introductory undergraduate course. It assumes students have had multivariable calculus. A second goal of this text is to demonstrate the intimate relationship of linear algebra to applications/computations. A rigorous presentation has been maintained. A third reason for writing this text is to present, in the first half of the course, the very important topic on singular value decomposition, SVD. This is done by first restricting consideration to real matrices and vector spaces. The general inner product vector spaces are considered starting in the middle of the text. The text has a number of applications. These are to motivate the student to study the linear algebra topics. Also, the text has a number of computations. MATLAB® is used, but one could modify these codes to other programming languages. These are either to simplify some linear algebra computation, or to model a particular application.}, publisher={Chapman and Hall/CRC}, author={White, Robert E.}, year={2023}, month={Apr} } @misc{rieger_allen_bystricky_chen_colopy_cui_gonzalez_liu_white_everett_et al._2018, title={Improving the generation and selection of virtual populations in quantitative systems pharmacology models}, volume={139}, ISSN={["0079-6107"]}, DOI={10.1016/j.pbiomolbio.2018.06.002}, abstractNote={Quantitative systems pharmacology (QSP) models aim to describe mechanistically the pathophysiology of disease and predict the effects of therapies on that disease. For most drug development applications, it is important to predict not only the mean response to an intervention but also the distribution of responses, due to inter-patient variability. Given the necessary complexity of QSP models, and the sparsity of relevant human data, the parameters of QSP models are often not well determined. One approach to overcome these limitations is to develop alternative virtual patients (VPs) and virtual populations (Vpops), which allow for the exploration of parametric uncertainty and reproduce inter-patient variability in response to perturbation. Here we evaluated approaches to improve the efficiency of generating Vpops. We aimed to generate Vpops without sacrificing diversity of the VPs' pathophysiologies and phenotypes. To do this, we built upon a previously published approach (Allen et al., 2016) by (a) incorporating alternative optimization algorithms (genetic algorithm and Metropolis-Hastings) or alternatively (b) augmenting the optimized objective function. Each method improved the baseline algorithm by requiring significantly fewer plausible patients (precursors to VPs) to create a reasonable Vpop.}, journal={PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY}, author={Rieger, Theodore R. and Allen, Richard J. and Bystricky, Lukas and Chen, Yuzhou and Colopy, Glen Wright and Cui, Yifan and Gonzalez, Angelica and Liu, Yifei and White, R. D. and Everett, R. A. and et al.}, year={2018}, month={Nov}, pages={15–22} } @article{white_2011, title={Identification of hazards with impulsive sources}, volume={88}, ISSN={["1029-0265"]}, DOI={10.1080/00207161003718682}, abstractNote={Given some observations downstream can one determine the location and intensities of point sources of a hazard (pollutant chemical or biological)? The unknown concentrations are governed by the diffusion-advection partial differential equation. The corresponding algebraic system is studied. The fixed location problem is considered using reordering, the Schur complement and nonnegative least squares. A nonlinear problem is proposed, and an iterative method is formulated based on nonnegative least squares and Newton's method. The variable location problem is tackled with simulated annealing. The complexities of controlling aquatic populations, which are nonlinear, time-dependent and have multiple sources, will be illustrated.}, number={4}, journal={INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS}, author={White, Robert E.}, year={2011}, pages={762–780} } @article{white_2009, title={Populations with impulsive culling: control and identification}, volume={86}, ISSN={["1029-0265"]}, DOI={10.1080/00207160802163686}, abstractNote={This paper is a numerical study of populations with dispersion (Fickian diffusion) in one or two directions and with a finite number of impulsive culling sites. The intensities and locations of the culling sites are used for optimal control of the population density. The identifications of the model parameters and location of the culling sites are determined from the given population density data. The Levenberg–Marquardt, variation of the simulated-annealing and semilinear-SOR algorithms are used.}, number={12}, journal={INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS}, author={White, Robert E.}, year={2009}, pages={2143–2164} } @book{white_2004, title={Computational mathematics: Models, methods, and analysis with MATLAB and MPI}, ISBN={1584883642}, publisher={Boca Raton, Fla.: Chapman & Hall/CRC}, author={White, R. E.}, year={2004} } @article{white_2000, title={Domain decomposition splittings}, volume={316}, ISSN={["0024-3795"]}, DOI={10.1016/S0024-3795(00)00016-1}, abstractNote={Domain decomposition splittings have the form A=B−C, where B has a nonzero arrow pattern. By using Schur complement one can study these splittings for both the symmetric positive-definite (SPD) and the M-matrix cases. Convergence results and some comparison results will be given.}, number={1-3}, journal={LINEAR ALGEBRA AND ITS APPLICATIONS}, author={White, RE}, year={2000}, month={Sep}, pages={105–112} } @article{white_2000, title={Multisplitting methods: Optimal schemes for the unknowns in a given overlap}, volume={22}, ISSN={["0895-4798"]}, DOI={10.1137/S0895479898334678}, abstractNote={Consider a linear algebraic problem where the set of unknowns is a union of subsets. Let the coefficient matrix have a splitting associated with each subset. The traditional multisplitting method forms a weighted sum, over the overlapping unknowns, of the iterates for each such splitting to obtain a single parallel iterative method. An optimal alternative to the weighted sums will be presented. Convergence of this new form of multisplitting (MS) method can be studied for both symmetric positive definite (SPD) matrices and M-matrices. Applications to PDEs and the equilibrium equations for fluid flow in a driven cavity will be presented.}, number={2}, journal={SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS}, author={White, RE}, year={2000}, month={Sep}, pages={554–568} }