# Talks on Optimization

### From Wikimization

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(→Sampling Theory and Practice: 50 Ways to Sample your Signal) |
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[http://www.convexoptimization.com/TOOLS/sampling_sparsity.ppt Martin Vetterli, EPFL & UC Berkeley] (10MByte PowerPoint) | [http://www.convexoptimization.com/TOOLS/sampling_sparsity.ppt Martin Vetterli, EPFL & UC Berkeley] (10MByte PowerPoint) | ||

- | == A Feasible Method for Optimization with <math>\|x\|^2\!= | + | == A Feasible Method for Optimization with <math>\|x\|^2\!=1</math> or <math>\,X^TX\!=I</math> == |

[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] | [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] | ||

## Current revision

# 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)

## A Feasible Method for Optimization with or

## Rigidity and Localization: An Optimization Perspective

## Explicit Sensor Network Localization using Semidefinite Programming and Facial Reduction

## 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

## Combining Geometry and Combinatorics: A Unified Approach to Sparse Signal Recovery

Presented by Anna Gilbert at the Applied Mathematics Seminar, Stanford University, October 3, 2008

## Compressed Sensing with Contiguous Fourier Measurements

## Optimization Problems in Compressed Sensing

## Compressed Sensing in Astronomy

## Highly Undersampled 0-Norm Reconstruction

Presented by Christine Law at Lucas Center for Imaging, Stanford University, July 9, 2008 (771KByte PowerPoint)

## Nonconvex Compressive Sensing

## Interior-Point Methods per l’Ottimizzazione Conica: SOCP e SDP

## Bregman Iterative Algorithms for L1 Minimization with Applications to Compressed Sensing

Presented by Stanley Osher with W. Yin, D. Goldfarb, & J. Darbon at the iCME Colloquium (CME 500), Stanford University, December 3, 2007 (400KByte PowerPoint)