The
Compressive Sensing Workshop that took place on February 25 & 26, 2009 at Duke University was jointly organized by
Lawrence Carin (Duke) and Gregory Arnold (AFRL), who are affiliated with the AFRL ATR Center in Dayton, Ohio. The local Duke hosts for the workshop were
Lawrence Carin,
David Brady,
Mauro Maggioni,
Xiaobai Sun, and
Rebecca Willet.
Lawrence Carin has been able to get most of the presentations from the presenters and posted them on the workshop site, here they are, enjoy the reading. There were few surprises and I'll talk about them later.
Ronald Coifman - Compressed Sensing, Intrinsic Variables and Diffusion Geometries Stanley Osher - Bregmanized Methods for Sparse Reconstruction and Restoration Rama Chellappa and Volkan Cevher - Applications of Compressed Sensing Concepts to Some Computer Vision Problems Guillermo Sapiro - Learning Sparse Representations to Restore, Classify and Sense Images & VideoMartin Wainwright - Graphical Model Selection in High-dimensions: Trade-offs Between Computational and Statistical EfficiencyMario Figueiredo - Iterative Shrinkage/Thresholding Algorithms: Some History and Recent Development
Lee Potter - Bayes to the Bone: Sparse Linear Regression with Limited Data Kevin Murphy - Learning Graph Structures with Unknown Blocks Robert Calderbank - Deterministic Compressive Sensing Matrices Rob Nowak - Distilled Sensing: The Power of Adaptivity Rick Chartrand - Fast Algorithms for Nonconvex Compressive Sensing Joel Tropp - Beyond Nyquist: Efficient Sampling of Sparse, Bandlimited Signals Michael Lustig - Frontiers in Rapid MRI: Parallel Imaging and Compressed Sensing Mark Neifeld - Adaptation for Task-Specific Compressive Sensing Kevin Kelly - Micromirror-based Compressive Imaging and Spectroscopy David Brady - Coding and Regularization in Optical Sensor Forward and Inverse Models Venkatesh Saligrama - Noisy Group Testing and Boolean Compressed Sensing Yonina Eldar - Beyond Nyquist: Compressed Sensing of Analog Signals Justin Romberg - Multiple Channel Estimation and Compressive Sensing Donald Goldfarb - Fixed Point and Bregman Iterative Methods for Matrix Rank Minimization Wotao Yin - Enhanced Compressed Sensing Based on Iterative Support Detection Thomas Blumensath - Iterative Hard Thresholding: Theory and Practice Richard Baraniuk - Model-based Compressive Sensing Rebecca Willet - Compressed Sensing in Low-Light Imaging George Papanicolaou - Resolution and Robustness of Array Imaging Algorithms Viewed with Compressive Sensing in MindEdward Bosch - Hyperspectral Imagery and Compressive Sensing Myron Brown - LIDAR and Compressive Sensing James McClellan - Compressive Sensing Data Acquisition and Imaging for GPR Mathias Seeger - Compressed Sensing for Medical ImagingJian Li - On Sparse Bayesian Learning and Iterative Adaptive Approach David Wipf - Latent Variable Bayesian Models for Promoting Sparsity Lawrence Carin - Putting Compression into Compressive SensingImage Credit: NASA/JPL/Space Science Institute,
Pandora, a moon of Saturn taken the day before the first day of the workshop.
The Compressive Sensing Workshop that took place on February 25 & 26, 2009 at Duke University was jointly organized by Lawrence Carin (Duke) and Gregory Arnold (AFRL), who are affiliated with the AFRL ATR Center in Dayton, Ohio. The local Duke hosts for the workshop were Lawrence Carin, David Brady, Mauro Maggioni, Xiaobai Sun, and Rebecca Willet.
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