v2009.01.01 - Convex Optimization
Share Embed Flag
Download ePaper

v2009.01.01 - Convex Optimization

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

convexoptimization.com
from convexoptimization.com More from this publisher
10.03.2015 Views

744 BIBLIOGRAPHY [320] È. B. Vinberg. The theory of convex homogeneous cones. Transactions of the Moscow Mathematical Society, 12:340–403, 1963. American Mathematical Society and London Mathematical Society joint translation, 1965. [321] Marie A. Vitulli. A brief history of linear algebra and matrix theory, 2004. darkwing.uoregon.edu/∼vitulli/441.sp04/LinAlgHistory.html [322] John von Neumann. Functional Operators, Volume II: The Geometry of Orthogonal Spaces. Princeton University Press, 1950. Reprinted from mimeographed lecture notes first distributed in 1933. [323] Michael B. Wakin, Jason N. Laska, Marco F. Duarte, Dror Baron, Shriram Sarvotham, Dharmpal Takhar, Kevin F. Kelly, and Richard G. Baraniuk. An architecture for compressive imaging. In Proceedings of the IEEE International Conference on Image Processing (ICIP), pages 1273–1276, October 2006. http://www.dsp.rice.edu/cs/CSCam-ICIP06.pdf [324] Roger Webster. Convexity. Oxford University Press, 1994. [325] Kilian Q. Weinberger and Lawrence K. Saul. Unsupervised learning of image manifolds by semidefinite programming. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 2, pages 988–995, 2004. http://www.cs.ucsd.edu/∼saul/papers/sde cvpr04.pdf [326] Eric W. Weisstein. Mathworld – A Wolfram Web Resource, 2007. http://mathworld.wolfram.com/search [327] Bernard Widrow and Samuel D. Stearns. Adaptive Signal Processing. Prentice-Hall, 1985. [328] Norbert Wiener. On factorization of matrices. Commentarii Mathematici Helvetici, 29:97–111, 1955. [329] Ami Wiesel, Yonina C. Eldar, and Shlomo Shamai (Shitz). Semidefinite relaxation for detection of 16-QAM signaling in MIMO channels. IEEE Signal Processing Letters, 12(9):653–656, September 2005. [330] Michael P. Williamson, Timothy F. Havel, and Kurt Wüthrich. Solution conformation of proteinase inhibitor IIA from bull seminal plasma by 1 H nuclear magnetic resonance and distance geometry. Journal of Molecular Biology, 182:295–315, 1985. [331] Willie W. Wong. Cayley-Menger determinant and generalized N-dimensional Pythagorean theorem, November 2003. Application of Linear Algebra: Notes on Talk given to Princeton University Math Club. http://www.princeton.edu/∼wwong/papers/gp-r.pdf [332] William Wooton, Edwin F. Beckenbach, and Frank J. Fleming. Modern Analytic Geometry. Houghton Mifflin, 1975.

[333] Margaret H. Wright. The interior-point revolution in optimization: History, recent developments, and lasting consequences. Bulletin of the American Mathematical Society, 42(1):39–56, January 2005. [334] Stephen J. Wright. Primal-Dual Interior-Point Methods. SIAM, 1997. [335] Shao-Po Wu. max-det Programming with Applications in Magnitude Filter Design. A dissertation submitted to the department of Electrical Engineering, Stanford University, December 1997. [336] Shao-Po Wu and Stephen Boyd. sdpsol: A parser/solver for semidefinite programs with matrix structure. In Laurent El Ghaoui and Silviu-Iulian Niculescu, editors, Advances in Linear Matrix Inequality Methods in Control, chapter 4, pages 79–91. SIAM, 2000. http://www.stanford.edu/∼boyd/sdpsol.html [337] Shao-Po Wu, Stephen Boyd, and Lieven Vandenberghe. FIR filter design via spectral factorization and convex optimization, 1997. http://www.stanford.edu/∼boyd/papers/magdes.html [338] Naoki Yamamoto and Maryam Fazel. A computational approach to quantum encoder design for purity optimization, 2006. http://arxiv.org/abs/quant-ph/0606106 [339] David D. Yao, Shuzhong Zhang, and Xun Yu Zhou. Stochastic linear-quadratic control via primal-dual semidefinite programming. SIAM Review, 46(1):87–111, March 2004. Erratum: p.209 herein. [340] Yinyu Ye. Semidefinite programming for Euclidean distance geometric optimization. Lecture notes, 2003. http://www.stanford.edu/class/ee392o/EE392o-yinyu-ye.pdf [341] Yinyu Ye. Convergence behavior of central paths for convex homogeneous self-dual cones, 1996. http://www.stanford.edu/∼yyye/yyye/ye.ps [342] Yinyu Ye. Interior Point Algorithms: Theory and Analysis. Wiley, 1997. [343] D. C. Youla. Mathematical theory of image restoration by the method of convex projection. In Henry Stark, editor, Image Recovery: Theory and Application, chapter 2, pages 29–77. Academic Press, 1987. [344] Fuzhen Zhang. Matrix Theory: Basic Results and Techniques. Springer-Verlag, 1999. [345] Günter M. Ziegler. Kissing numbers: Surprises in dimension four. Emissary, pages 4–5, Spring 2004. http://www.msri.org/communications/emissary 2001 Jon Dattorro. CO&EDG version 2009.01.01. All rights reserved. Citation: Jon Dattorro, Convex Optimization & Euclidean Distance Geometry, Meboo Publishing USA, 2005. 745

744 BIBLIOGRAPHY<br />

[320] È. B. Vinberg. The theory of convex homogeneous cones. Transactions of the<br />

Moscow Mathematical Society, 12:340–403, 1963. American Mathematical Society<br />

and London Mathematical Society joint translation, 1965.<br />

[321] Marie A. Vitulli. A brief history of linear algebra and matrix theory, 2004.<br />

darkwing.uoregon.edu/∼vitulli/441.sp04/LinAlgHistory.html<br />

[322] John von Neumann. Functional Operators, Volume II: The Geometry of Orthogonal<br />

Spaces. Princeton University Press, 1950. Reprinted from mimeographed lecture<br />

notes first distributed in 1933.<br />

[323] Michael B. Wakin, Jason N. Laska, Marco F. Duarte, Dror Baron, Shriram<br />

Sarvotham, Dharmpal Takhar, Kevin F. Kelly, and Richard G. Baraniuk. An<br />

architecture for compressive imaging. In Proceedings of the IEEE International<br />

Conference on Image Processing (ICIP), pages 1273–1276, October 2006.<br />

http://www.dsp.rice.edu/cs/CSCam-ICIP06.pdf<br />

[324] Roger Webster. <strong>Convex</strong>ity. Oxford University Press, 1994.<br />

[325] Kilian Q. Weinberger and Lawrence K. Saul. Unsupervised learning of image<br />

manifolds by semidefinite programming. In Proceedings of the IEEE Computer<br />

Society Conference on Computer Vision and Pattern Recognition, volume 2, pages<br />

988–995, 2004.<br />

http://www.cs.ucsd.edu/∼saul/papers/sde cvpr04.pdf<br />

[326] Eric W. Weisstein. Mathworld – A Wolfram Web Resource, 2007.<br />

http://mathworld.wolfram.com/search<br />

[327] Bernard Widrow and Samuel D. Stearns. Adaptive Signal Processing. Prentice-Hall,<br />

1985.<br />

[328] Norbert Wiener. On factorization of matrices. Commentarii Mathematici Helvetici,<br />

29:97–111, 1955.<br />

[329] Ami Wiesel, Yonina C. Eldar, and Shlomo Shamai (Shitz). Semidefinite relaxation<br />

for detection of 16-QAM signaling in MIMO channels. IEEE Signal Processing<br />

Letters, 12(9):653–656, September 2005.<br />

[330] Michael P. Williamson, Timothy F. Havel, and Kurt Wüthrich. Solution<br />

conformation of proteinase inhibitor IIA from bull seminal plasma by 1 H nuclear<br />

magnetic resonance and distance geometry. Journal of Molecular Biology,<br />

182:295–315, 1985.<br />

[331] Willie W. Wong. Cayley-Menger determinant and generalized N-dimensional<br />

Pythagorean theorem, November 2003. Application of Linear Algebra: Notes on<br />

Talk given to Princeton University Math Club.<br />

http://www.princeton.edu/∼wwong/papers/gp-r.pdf<br />

[332] William Wooton, Edwin F. Beckenbach, and Frank J. Fleming. Modern Analytic<br />

Geometry. Houghton Mifflin, 1975.

logo

products

Resources

Company

Terms of service
Privacy policy
Cookie policy
Cookie settings
Imprint
Change language
Made with love in Switzerland
© 2024 Yumpu.com all rights reserved

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!