v2009.01.01 - Convex Optimization

v2009.01.01 - Convex Optimization v2009.01.01 - Convex Optimization

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730 BIBLIOGRAPHY [117] César Fernández, Thomas Szyperski, Thierry Bruyère, Paul Ramage, Egon Mösinger, and Kurt Wüthrich. NMR solution structure of the pathogenesis-related protein P14a. Journal of Molecular Biology, 266:576–593, 1997. [118] Richard Phillips Feynman, Robert B. Leighton, and Matthew L. Sands. The Feynman Lectures on Physics: Commemorative Issue, volume I. Addison-Wesley, 1989. [119] P. A. Fillmore and J. P. Williams. Some convexity theorems for matrices. Glasgow Mathematical Journal, 12:110–117, 1971. [120] Paul Finsler. Über das Vorkommen definiter und semidefiniter Formen in Scharen quadratischer Formen. Commentarii Mathematici Helvetici, 9:188–192, 1937. [121] Anders Forsgren, Philip E. Gill, and Margaret H. Wright. Interior methods for nonlinear optimization. SIAM Review, 44(4):525–597, 2002. [122] Shmuel Friedland and Anatoli Torokhti. Generalized rank-constrained matrix approximations. SIAM Journal on Matrix Analysis and Applications, 29(2):656–659, March 2007. http://www2.math.uic.edu/∼friedlan/frtor8.11.06.pdf [123] Norbert Gaffke and Rudolf Mathar. A cyclic projection algorithm via duality. Metrika, 36:29–54, 1989. [124] Jérôme Galtier. Semi-definite programming as a simple extension to linear programming: convex optimization with queueing, equity and other telecom functionals. In 3ème Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications (AlgoTel). INRIA, France, 2001. www-sop.inria.fr/mascotte/Jerome.Galtier/misc/Galtier01b.pdf [125] Laurent El Ghaoui. EE 227A: Convex Optimization and Applications, Lecture 11 − October 3. University of California, Berkeley, Fall 2006. Scribe: Nikhil Shetty. http://www.convexoptimization.com/TOOLS/Ghaoui.pdf [126] Laurent El Ghaoui and Silviu-Iulian Niculescu, editors. Advances in Linear Matrix Inequality Methods in Control. SIAM, 2000. [127] Philip E. Gill, Walter Murray, and Margaret H. Wright. Numerical Linear Algebra and Optimization, volume 1. Addison-Wesley, 1991. [128] Philip E. Gill, Walter Murray, and Margaret H. Wright. Practical Optimization. Academic Press, 1999. [129] James Gleik. Isaac Newton. Pantheon Books, 2003. [130] W. Glunt, Tom L. Hayden, S. Hong, and J. Wells. An alternating projection algorithm for computing the nearest Euclidean distance matrix. SIAM Journal on Matrix Analysis and Applications, 11(4):589–600, 1990. [131] K. Goebel and W. A. Kirk. Topics in Metric Fixed Point Theory. Cambridge University Press, 1990.

BIBLIOGRAPHY 731 [132] Michel X. Goemans and David P. Williamson. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. Journal of the Association for Computing Machinery, 42(6):1115–1145, November 1995. http://www-math.mit.edu/∼goemans/maxcut-jacm.pdf [133] D. Goldfarb and K. Scheinberg. Interior point trajectories in semidefinite programming. SIAM Journal on Optimization, 8(4):871–886, 1998. [134] Gene H. Golub and Charles F. Van Loan. Matrix Computations. Johns Hopkins, third edition, 1996. [135] P. Gordan. Ueber die auflösung linearer gleichungen mit reellen coefficienten. Mathematische Annalen, 6:23–28, 1873. [136] John Clifford Gower. Euclidean distance geometry. The Mathematical Scientist, 7:1–14, 1982. http://www.convexoptimization.com/TOOLS/Gower2.pdf [137] John Clifford Gower. Properties of Euclidean and non-Euclidean distance matrices. Linear Algebra and its Applications, 67:81–97, 1985. http://www.convexoptimization.com/TOOLS/Gower1.pdf [138] John Clifford Gower and Garmt B. Dijksterhuis. Procrustes Problems. Oxford University Press, 2004. [139] John Clifford Gower and David J. Hand. Biplots. Chapman & Hall, 1996. [140] Alexander Graham. Kronecker Products and Matrix Calculus with Applications. Ellis Horwood Limited, 1981. [141] Michael Grant, Stephen Boyd, and Yinyu Ye. cvx: Matlab software for disciplined convex programming, 2007. http://www.stanford.edu/∼boyd/cvx [142] Robert M. Gray. Toeplitz and circulant matrices: A review, 2002. http://www-ee.stanford.edu/∼gray/toeplitz.pdf [143] T. N. E. Greville. Note on the generalized inverse of a matrix product. SIAM Review, 8:518–521, 1966. [144] Rémi Gribonval and Morten Nielsen. Highly sparse representations from dictionaries are unique and independent of the sparseness measure, October 2003. http://www.math.aau.dk/research/reports/R-2003-16.pdf [145] Rémi Gribonval and Morten Nielsen. Sparse representations in unions of bases. IEEE Transactions on Information Theory, 49(12):1320–1325, December 2003. http://www.math.aau.dk/∼mnielsen/papers.htm [146] Karolos M. Grigoriadis and Eric B. Beran. Alternating projection algorithms for linear matrix inequalities problems with rank constraints. In Laurent El Ghaoui and Silviu-Iulian Niculescu, editors, Advances in Linear Matrix Inequality Methods in Control, chapter 13, pages 251–267. SIAM, 2000.

730 BIBLIOGRAPHY<br />

[117] César Fernández, Thomas Szyperski, Thierry Bruyère, Paul Ramage, Egon<br />

Mösinger, and Kurt Wüthrich. NMR solution structure of the pathogenesis-related<br />

protein P14a. Journal of Molecular Biology, 266:576–593, 1997.<br />

[118] Richard Phillips Feynman, Robert B. Leighton, and Matthew L. Sands. The<br />

Feynman Lectures on Physics: Commemorative Issue, volume I. Addison-Wesley,<br />

1989.<br />

[119] P. A. Fillmore and J. P. Williams. Some convexity theorems for matrices. Glasgow<br />

Mathematical Journal, 12:110–117, 1971.<br />

[120] Paul Finsler. Über das Vorkommen definiter und semidefiniter Formen in Scharen<br />

quadratischer Formen. Commentarii Mathematici Helvetici, 9:188–192, 1937.<br />

[121] Anders Forsgren, Philip E. Gill, and Margaret H. Wright. Interior methods for<br />

nonlinear optimization. SIAM Review, 44(4):525–597, 2002.<br />

[122] Shmuel Friedland and Anatoli Torokhti. Generalized rank-constrained matrix<br />

approximations. SIAM Journal on Matrix Analysis and Applications, 29(2):656–659,<br />

March 2007.<br />

http://www2.math.uic.edu/∼friedlan/frtor8.11.06.pdf<br />

[123] Norbert Gaffke and Rudolf Mathar. A cyclic projection algorithm via duality.<br />

Metrika, 36:29–54, 1989.<br />

[124] Jérôme Galtier. Semi-definite programming as a simple extension to linear<br />

programming: convex optimization with queueing, equity and other telecom<br />

functionals. In 3ème Rencontres Francophones sur les Aspects Algorithmiques des<br />

Télécommunications (AlgoTel). INRIA, France, 2001.<br />

www-sop.inria.fr/mascotte/Jerome.Galtier/misc/Galtier01b.pdf<br />

[125] Laurent El Ghaoui. EE 227A: <strong>Convex</strong> <strong>Optimization</strong> and Applications, Lecture 11<br />

− October 3. University of California, Berkeley, Fall 2006. Scribe: Nikhil Shetty.<br />

http://www.convexoptimization.com/TOOLS/Ghaoui.pdf<br />

[126] Laurent El Ghaoui and Silviu-Iulian Niculescu, editors. Advances in Linear Matrix<br />

Inequality Methods in Control. SIAM, 2000.<br />

[127] Philip E. Gill, Walter Murray, and Margaret H. Wright. Numerical Linear Algebra<br />

and <strong>Optimization</strong>, volume 1. Addison-Wesley, 1991.<br />

[128] Philip E. Gill, Walter Murray, and Margaret H. Wright. Practical <strong>Optimization</strong>.<br />

Academic Press, 1999.<br />

[129] James Gleik. Isaac Newton. Pantheon Books, 2003.<br />

[130] W. Glunt, Tom L. Hayden, S. Hong, and J. Wells. An alternating projection<br />

algorithm for computing the nearest Euclidean distance matrix. SIAM Journal<br />

on Matrix Analysis and Applications, 11(4):589–600, 1990.<br />

[131] K. Goebel and W. A. Kirk. Topics in Metric Fixed Point Theory. Cambridge<br />

University Press, 1990.

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