From Wikimization
Optimization with or Fast Constraint-Preserving Algorithms
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
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
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
Presented by Christine Law with Gary Glover at the Linear Algebra Seminar, University of California, Berkeley, February 4, 2009 (5MB)
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
Presented by Jean-François Mercier with Laurent Demanet and George Papanicolaou at the Applied Mathematics Seminar, Stanford University, July 21, 2008
Optimization Problems in Compressed Sensing
by Jalal Fadili, CNRS, ENSI Caen France, at the Applied Mathematics Seminar, Stanford University, July 21, 2008
Compressed Sensing in Astronomy
Presented by Jean-Luc Starck with Jérôme Bobin at the Applied Mathematics Seminar, Stanford University, July 21, 2008
Highly Undersampled 0-Norm Reconstruction
Presented by Christine Law at Lucas Center for Imaging, Stanford University, July 9, 2008 (771KByte)
Nonconvex Compressive Sensing
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
IPM per l’Ottimizzazione Conica: SOCP e SDP
Presented by Andrea Cassioli, Dipartimento di Sistemi e Informatica, Universitá di Firenze, May 28, 2008
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)