Optimization Videos

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1 Compressive Sampling and Frontiers in Signal Processing
- 1.1 Compressive Sampling, Compressed Sensing - Emmanuel Candes, University of Minnesota, Summer 2007
2 Introduction to Magnetic Resonance Imaging (MRI)
- 2.1 Leon Axel (New York University), Steen Moeller (University of Minnesota)
3 Compressive Sampling, Compressed Sensing
- 3.1 Richard Baraniuk (Rice University) Summer 2007
4 Chromosome structure, University of California, San Diego
- 4.1 Ronan Fleming
5 International Society for Magnetic Resonance in Medicine (ISMRM Toronto 2008)
- 5.1 Randy Duensing & Feng Huang
6 Convex Optimization, Stanford University
- 6.1 Stephen Boyd

Compressive Sampling and Frontiers in Signal Processing

Compressive Sampling, Compressed Sensing - Emmanuel Candes, University of Minnesota, Summer 2007

(requires RealPlayer to watch)

June 4 2007 Sparsity and the l1 norm

June 5 2007 Underdetermined Systems of Linear Equations (Audio begins 4 minutes into film.)

Norms.

Early work by pioneers ( $LaTeX: \approx$ 16 minutes into film).

Deconvolution ( $LaTeX: \approx$ 30 minutes into film).

Lasso, Basis Pursuit ( $LaTeX: \approx$ 38 minutes in).

Wavelets, Curvelets, Ridgelets, sinusoids ( $LaTeX: \approx$ 55 minutes in).

Overcomplete Dictionary ( $LaTeX: \approx$ 57 minutes in).

Basis Pursuit ( $LaTeX: \approx$ 1:03 hours in).

Feature separation ( $LaTeX: \approx$ 1:12 hours in).

Barbara, Jean-Luc Stark ( $LaTeX: \approx$ 1:15 hours in).

Magnetic Resonance Imaging (MRI) ( $LaTeX: \approx$ 1:16 hours in).

Sample rate ( $LaTeX: \approx$ 1:36 hours in).

June 6 2007 Sparsity and Incoherence (If you only watch one Candes video, this is it.)

Recovery of Dirac comb, derivation of minimum sampling rate ( $LaTeX: \approx$ 11 minutes into film).

4:1 sample to sparsity rule ( $LaTeX: \approx$ 21 minutes into film).

Candes' Matlab code ( $LaTeX: \approx$ 25 minutes in).

Fundamental premises of Compressed Sensing: sparsity and incoherence ( $LaTeX: \approx$ 29 minutes in).

June 7 2007 The Uniform Uncertainty Principle

June 8 2007 The Role of Probability in Compressed Sensing

June 11 2007 Part 1 - Robust Compressed Sensing and Connections with Statistics (Audio back at 17 minutes into film.)

June 12 2007 Part 2 - Robust Compressed Sensing and Connections with Statistics

Matlab ( $LaTeX: \approx$ 1:15).

MRI phantom with noise using Dantzig ( $LaTeX: \approx$ 1:28).

Imaging fuel cells ( $LaTeX: \approx$ 1:31).

Subsampling ( $LaTeX: \approx$ 1:36).

June 13 2007 Connections with Information and Coding Theory

error correction (since the beginning).

Matlab decode ( $LaTeX: \approx$ 20 min in).

second error corruption model: gross error + quantization error ( $LaTeX: \approx$ 29 min in).

Connection with the Sparse Recovery Problem ( $LaTeX: \approx$ 57 min in).

Reed-Solomon code ( $LaTeX: \approx$ 1:08 min in).

Matlab for Reed-Solomon code ( $LaTeX: \approx$ 1:26 min in).

June 14 2007 Modern Convex Optimization

Unconstrained Minimization ( $LaTeX: \approx$ 11 min in).

Matlab example for Gradient Descent with exact Line Search ( $LaTeX: \approx$ 19 min in).

Exact line search vs. Backtracking line search ( $LaTeX: \approx$ 22 min in).

Newton Step ( $LaTeX: \approx$ 26 min in).

Self Concordance ( $LaTeX: \approx$ 35 min in).

Equality Constrained Minimization ( $LaTeX: \approx$ 43 min in).

Barrier function ( $LaTeX: \approx$ 47 min in).

Central path ( $LaTeX: \approx$ 53 min in).

Complexity analysis ( $LaTeX: \approx$ 1:14).

Matlab for log-barrier ( $LaTeX: \approx$ 1:25).

Primal-dual interior point methods ( $LaTeX: \approx$ 1:29).

June 15 2007 Topics and Applications of Compressive Sampling

Beyond L1 minimization ( $LaTeX: \approx$ 3 min in).

Reweighted TV for MRI phantom: recover using m=1.2S (S is number of non zero gradient terms) ( $LaTeX: \approx$ 14 min in).

Overcomplete representations ( $LaTeX: \approx$ 19 min in).

Geometric separation: Cartoon + Texture ( $LaTeX: \approx$ 22 min in).

L1 synthesis vs. analysis for CS ( $LaTeX: \approx$ 28 min in).

Pulse reconstruction using L1 synthesis, L1 analysis and reweighted L1 analysis( $LaTeX: \approx$ 36 min).

ADC: nonuniform sampler vs. random pre-integrator ( $LaTeX: \approx$ 48 min).

Introduction to Magnetic Resonance Imaging (MRI)

Leon Axel (New York University), Steen Moeller (University of Minnesota)

June 5, 2007

Compressive Sampling, Compressed Sensing

Richard Baraniuk (Rice University) Summer 2007

June 11, 2007 Compressive sensing for time signals: Analog to information conversion

June 12, 2007 Compressive sensing for detection and classification problems

June 12, 2007 Multi-signal, distributed compressive sensing

June 13, 2007 Compressive imaging with a single pixel camera

Chromosome structure, University of California, San Diego

Ronan Fleming

Auto-correlation coefficients (6MB video) from Chromosome structure via Euclidean Distance Matrices.

International Society for Magnetic Resonance in Medicine (ISMRM Toronto 2008)

Randy Duensing & Feng Huang

(requires Adobe Flash Player)

Objective Comparison of Alternate Reconstruction Strategies: An Unmet Need

Username: 44141
Password: Law

Convex Optimization, Stanford University

Stephen Boyd

Tutorials for a graduate level course, 2008

Retrieved from "http://www.convexoptimization.com/wikimization/index.php/Optimization_Videos"

@@ Line 74: / Line 74: @@
 ==Compressive Sampling, Compressed Sensing==
 === Richard Baraniuk (Rice University) Summer 2007 ===
-[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk2.6-11-07.ram June 11, 2007]
+[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk2.6-11-07.ram June 11, 2007] &nbsp;'''Compressive sensing for time signals: Analog to information conversion'''
-[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk1.6-12-07.ram June 12, 2007]
+[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk1.6-12-07.ram June 12, 2007] &nbsp;'''Compressive sensing for detection and classification problems'''
-[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk2.6-12-07.ram June 12, 2007]
-[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk6-13-07.ram June 13, 2007]
+[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk2.6-12-07.ram June 12, 2007] &nbsp;'''Multi-signal, distributed compressive sensing'''
+[http://www.ima.umn.edu/recordings/New_Directions_Short_Course/ND6.4-15.07/baraniuk6-13-07.ram June 13, 2007] &nbsp;'''Compressive imaging with a single pixel camera'''
 == Chromosome structure, University of California, San Diego ==