Description
- Provides historical perspective on the problems studied by optimizers, statisticians, and geometric functional analysts.
- Demonstrates the huge computational savings possible by exploiting simple updates for the determinant and the inverse after a rank-one update.
- Highlights the difficulties in algorithms when related problems are studied that do not allow simple updates at each iteration.
- Gives rigorous analyses of the proposed algorithms, MATLAB codes, and computational results.
About the Author
Michael J. Todd is Leon C. Welch Professor Emeritus of the School of Operations Research and Information Engineering at Cornell University. He received a Guggenheim Fellowship (1980-1981), a Sloan Research Fellowship (1981-1985), the George B. Dantzig Prize (1988) and the John von Neumann Theory Prize (2003). He is an INFORMS Fellow and a SIAM Fellow. He has served on the editorial boards of Mathematics of Operations Research, Operations Research, and the SIAM Journal on Optimization. He was also Managing Editor of Foundations of Computational Mathematics and has served on the boards of Acta Numerica and Foundations and Trends in Optimization. He is the author of one book and the co-editor of five others.
Book Information
ISBN 9781611974379
Author Michael J. Todd
Format Paperback
Page Count 164
Imprint Society for Industrial & Applied Mathematics,U.S.
Publisher Society for Industrial & Applied Mathematics,U.S.
Weight(grams) 385g