# Talks on Optimization

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Line 1: Line 1: + = Slides, Powerpoint, and PDF Presentations  ([http://www.convexoptimization.com/wikimization/index.php/Optimization_Videos More talks, in video format]) = + + == Sampling Theory and Practice: 50 Ways to Sample your Signal == + [http://www.convexoptimization.com/TOOLS/sampling_sparsity.ppt Martin Vetterli, EPFL & UC Berkeley]  (10MByte PowerPoint) + + == A Feasible Method for Optimization with [itex]\|x\|^2\!=1[/itex] or [itex]\,X^TX\!=I[/itex] == + [http://dl.dropbox.com/u/7103424/Tai/Talk3.pdf Zaiwen Wen, Wotao Yin, resp: NSF Postdoc with UCLA and Rice, Department of Computational and Applied Mathematics (CAAM) Rice University, October 2010] + + == Rigidity and Localization: An Optimization Perspective == + [http://www.convexoptimization.com/TOOLS/Stanford-OR-Seminar-web.pdf Anthony Man-Cho So, Dept. of Systems Engineering & Engineering Management, Chinese University of Hong Kong, at Operations Research Seminar, Stanford University, March 15, 2010] + + == Explicit Sensor Network Localization using Semidefinite Programming and Facial Reduction == + [http://www.convexoptimization.com/TOOLS/Wolkowicz_completion_slides.pdf Nathan Krislock and Henry Wolkowicz, Dept. of Combinatorics and Optimization, University of Waterloo, at ICME Stanford University Friday Oct. 30, 2009] + + == Toward 0-norm Reconstruction, and a Nullspace Technique for Compressive Sampling == + [http://www.convexoptimization.com/TOOLS/linear3.ppt Presented by Christine Law with Gary Glover at the Linear Algebra Seminar, University of California, Berkeley, February 4, 2009]  (5MByte PowerPoint) + Also presented by Christine Law with Gary Glover at the Linear Algebra and Optimization Seminar (CME510), iCME, Stanford University, November 19, 2008 + + == Combining Geometry and Combinatorics: A Unified Approach to Sparse Signal Recovery == + [http://www.convexoptimization.com/TOOLS/Anna.pdf Presented by Anna Gilbert at the Applied Mathematics Seminar, Stanford University, October 3, 2008] + == Compressed Sensing with Contiguous Fourier Measurements == == Compressed Sensing with Contiguous Fourier Measurements == [http://www.convexoptimization.com/TOOLS/mercier.pdf Presented by Jean-François Mercier with Laurent Demanet and George Papanicolaou at the Applied Mathematics Seminar, Stanford University, July 21, 2008] [http://www.convexoptimization.com/TOOLS/mercier.pdf Presented by Jean-François Mercier with Laurent Demanet and George Papanicolaou at the Applied Mathematics Seminar, Stanford University, July 21, 2008] Line 9: Line 30: == Highly Undersampled 0-Norm Reconstruction == == Highly Undersampled 0-Norm Reconstruction == - [http://www.convexoptimization.com/TOOLS/Law.ppt Presented by Christine Law at Lucas Center for Imaging, Stanford University, July 9, 2008]  (1.3MByte) + [http://www.convexoptimization.com/TOOLS/Law.ppt Presented by Christine Law at Lucas Center for Imaging, Stanford University, July 9, 2008]  (771KByte PowerPoint) - + - == Advances in Compressive Sensing for MRI == + - [http://www.convexoptimization.com/TOOLS/SIAM_IS08_short2.ppt Presented by Joshua Trzasko with Armando Manduca at the SIAM Conference on Imaging Science 2008, San Diego, California, July 7, 2008]  (15MByte) + == Nonconvex Compressive Sensing == == Nonconvex Compressive Sensing == [http://www.convexoptimization.com/TOOLS/Chartrand1.pdf Presented by Rick Chartrand with Valentina Staneva, Wotao Yin, & Kevin Vixie at the SIAM Conference on Imaging Science 2008, San Diego, California, July 7, 2008] [http://www.convexoptimization.com/TOOLS/Chartrand1.pdf Presented by Rick Chartrand with Valentina Staneva, Wotao Yin, & Kevin Vixie at the SIAM Conference on Imaging Science 2008, San Diego, California, July 7, 2008] - == Bregman Iterative Algorithms for L1 Minimization with Applications to Compressed Sensing == + == Interior-Point Methods per l’Ottimizzazione Conica: SOCP e SDP == - [http://www.convexoptimization.com/TOOLS/sjo-BregmanIteration10-07.ppt Presented by Stanley Osher with W. Yin, D. Goldfarb, & J. Darbon at the iCME Colloquium (CME 500), Stanford University, December 3, 2007]  (400KByte) + [http://www.convexoptimization.com/TOOLS/IPM_Lezione4.pdf Presented by Andrea Cassioli, Dipartimento di Sistemi e Informatica, Universitá di Firenze, May 28, 2008] - == Compressed Sensing: A Tutorial == + == Bregman Iterative Algorithms for L1 Minimization with Applications to Compressed Sensing == - [http://users.ece.gatech.edu/~justin/ssp2007/ssp07-cs-tutorial.pdf by Justin Romberg & Michael Wakin at IEEE 14th Workshop on Statistical Signal Processing, Madison Wisconsin, August 26, 2007] + [http://www.convexoptimization.com/TOOLS/sjo-BregmanIteration10-07.ppt Presented by Stanley Osher with W. Yin, D. Goldfarb, & J. Darbon at the iCME Colloquium (CME 500), Stanford University, December 3, 2007]  (400KByte PowerPoint)

# Slides, Powerpoint, and PDF Presentations  (More talks, in video format)

## Sampling Theory and Practice: 50 Ways to Sample your Signal

Martin Vetterli, EPFL & UC Berkeley  (10MByte PowerPoint)

## Toward 0-norm Reconstruction, and a Nullspace Technique for Compressive Sampling

Presented by Christine Law with Gary Glover at the Linear Algebra Seminar, University of California, Berkeley, February 4, 2009  (5MByte PowerPoint) Also presented by Christine Law with Gary Glover at the Linear Algebra and Optimization Seminar (CME510), iCME, Stanford University, November 19, 2008