Systems Optimization Laboratory

Stanford University
Dept of Management Science and Engineering (MS&E)

A few downloadable articles are collected here:

Y. Choi, C. Farhat, W. Murray, and M. Saunders. A practical factorization of a Schur complement for PDE-constrained distributed optimal control, J. Sci. Comput., 2014, DOI 10.1007/s10915-014-9976-0.

Jiyan Yang, Xiangrui Meng, and Michael W. Mahoney. Quantile regression for large-scale applications, SIAM J. Sci. Comput. 36:5 (2014) S78-S110.

Xiangrui Meng, Michael A. Saunders, and Michael W. Mahoney. LSRN: a parallel iterative solver for strongly over- or underdetermined systems, SIAM J. Sci. Comput. 36:2 (2014) C95-C118.

Y. Sun, R. M. T. Fleming, I. Thiele, and M. A. Saunders. Robust flux analysis of multiscale biochemical reaction networks, BMC Bioinformatics 14:240 (2013). Local copy: BMCBioinformatics2013robustFBA.pdf.

P. Berman, O. Levi, Y. Parmet, M. Saunders, and Z. Wiesman. Laplace inversion of low-resolution NMR relaxometry data using sparse representation methods, Concepts in Magnetic Resonance Part A 42:3 (2013) 72-88.
P. Berman, A. Leshem, O. Etziony, O. Levi, Y. Parmet, M. Saunders, and Z. Wiesman. Novel ¹H low field nuclear magnetic resonance applications for the field of biodiesel, Biotechnology for Biofuels 6:55, 20 pp (2013).

R. M. T. Fleming, C. M. Maes, M. A. Saunders, Y. Ye, B. Ø. Palsson. A variational principle for computing nonequilibrium fluxes and potentials in genome-scale biochemical networks, J. of Theoretical Biology 292, 71-77 (2012).

D. C.-L. Fong and M. A. Saunders. CG versus MINRES: An empirical comparison, SQU Journal for Science 17:1, 44-62 (2012).

S. P. Ponnapalli, M. A. Saunders, C. F. Van Loan, and O. Alter. A higher-order generalized singular value decomposition for comparison of global mRNA expression from multiple organisms, PLoS ONE 6(12):e28072, 1-11 (2011).

D. C.-L. Fong and M. A. Saunders, LSMR: An iterative algorithm for sparse least-squares problems, SIAM J. Sci. Comput. 33:5, 2950-2971, published electronically Oct 27, 2011.
Note: For Golub-Kahan bidiagonalization, Section 7.3 of the above paper reports ancillary results on reorthogonalizing either the left vectors or the right vectors or both. After the paper appeared, we became aware that the following article also reports the effectiveness of one-sided reorthogonalization:
H. D. Simon and H. Zha. Low-rank matrix approximation using the Lanczos bidiagonalization process with applications, SIAM J. Sci. Comput. 21:6, 2257-2274 (2000).

S.-C. T. Choi, C. C. Paige and M. A. Saunders. MINRES-QLP: A Krylov subspace method for indefinite or singular symmetric systems, SIAM J. Sci. Comput. 33:4, 1810-1836, published electronically Aug 4, 2011. (Winner of SIAM Linear Algebra Prize awarded by SIAM Activity Group on Linear Algebra, 2012 SIAM Conference on Applied Linear Algebra, Valencia, Spain, June 18-22, 2012.)

M. W. Carter, H. H. Jin, M. A. Saunders, and Y. Ye. SpaseLoc: An adaptive subproblem algorithm for scalable wireless sensor network localization, SIAM J. on Optimization 17(4), 1102-1128 (2006).

R. Tibshirani, M. A. Saunders, S. Rosset, J. Zhu, and K. Knight. Sparsity and smoothness via the fused lasso, J. Royal Statistical Society B 67(1), 91-108 (2005).

M. P. Friedlander and M. A. Saunders. A globally convergent linearly constrained Lagrangian method for nonlinear optimization, SIAM J. on Optimization 15(3), 863-897 (2005). (Winner of Best Paper Award, ICCOPT 1, RPI, NY, 2004.)

SIAM Review Editors, SIGEST Introduction to SNOPT paper, SIAM Review 47(1), 97 (2005).

P. E. Gill, W. Murray and M. A. Saunders. SNOPT: An SQP algorithm for large-scale constrained optimization, SIAM Review 47(1), 99-131 (2005).

M. Jacobsen, P. C. Hansen and M. A. Saunders. Subspace preconditioned LSQR for discrete ill-posed problems, BIT 43, 975-989 (2003).

S. S. Chen, D. L. Donoho, and M. A. Saunders. Atomic decomposition by Basis Pursuit, SIAM Review 43(1), 129-159 (2001).

G. Infanger. Monte Carlo (importance) sampling within a Benders decomposition algorithm for stochastic linear programs, Annals of Operations Research 39 69-95 (1992).

P. E. Gill, W. Murray, M. A. Saunders, and M. H. Wright (1989). A practical anti-cycling procedure for linearly constrained optimization, Math. Prog. 45, 437-474 (1989).

P. E. Gill, W. Murray, M. A. Saunders, J. A. Tomlin and M. H. Wright (1986). On projected Newton barrier methods for linear programming and an equivalence to Karmarkar's projective method, Math. Prog. 36, 183-209 (1986).

P. E. Gill, W. Murray, M. A. Saunders and M. H. Wright. Sparse matrix methods in optimization, SIAM J. on Scientific and Statistical Computing 5(3), 562-589 (1984).

C. C. Paige and M. A. Saunders. Towards a generalized singular value decomposition, SIAM J. Numer. Anal. 18(3), 398-405 (1981).

C. C. Paige and M. A. Saunders. Least squares estimation of discrete linear dynamic systems using orthogonal transformations, SIAM J. Numer. Anal. 14(2), 180-193 (1977).

P. E. Gill, G. H. Golub, W. Murray, and M. A. Saunders. Methods for modifying matrix factorizations, Mathematics of Computation 28(126), 505-535 (1974).