# Talks on Optimization

### From Wikimization

(Difference between revisions)

(→Toward 0-norm Reconstruction, and a Nullspace Technique for Compressive Sampling) |
|||

Line 21: | Line 21: | ||

== 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] (771KByte) | [http://www.convexoptimization.com/TOOLS/Law.ppt Presented by Christine Law at Lucas Center for Imaging, Stanford University, July 9, 2008] (771KByte) | ||

- | |||

- | == 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 == | ||

Line 33: | Line 30: | ||

== Bregman Iterative Algorithms for L1 Minimization with Applications to Compressed Sensing == | == Bregman Iterative Algorithms for L1 Minimization with Applications to Compressed Sensing == | ||

[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/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) | ||

- | |||

- | == Compressed Sensing: A Tutorial == | ||

- | [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] |

## Revision as of 08:46, 3 September 2009

# Slides, Powerpoint, and PDF Presentations

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

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)