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- Wavelet-domain Approximation and Compression of Piecewise Smooth Images
- Random Channel Coding and Blind Deconvolution M. Salman Asif, William Mantzel and Justin Romberg
- Encoding the p Ball from Limited Measurements Emmanuel Cand`es and Justin Romberg
- Compressed Sensing Phase Retrieval Matthew L. Moravecr, Justin K. Rombergg, and Richard G. Baraniukr
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- Efficient seismic forward modeling using simultaneous random sources and sparsity
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- Multiple Channel Estimation using Spectrally Random Probes
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- Efficient Seismic Forward Modeling using Simultaneous Random Sources and Sparsity
- Basis Pursuit with Sequential Measurements and Time Varying Signals
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- An Overview of Recent Results on the Identification of Sparse Channels Using Random Probes
- On the LASSO and Dantzig Selector Equivalence M. Salman Asif and Justin Romberg
- Multi-Camera Tracking on a Graph Using Markov Chain Monte Carlo
- Dynamic Updating for Sparse Time Varying Signals M. Salman Asif and Justin Romberg
- CAPTURING LIGHT FIELD TEXTURES FOR VIDEO CODING William Mantzel, Justin Romberg
- COMPRESSIVE SENSING OF PARAMETERIZED SHAPES IN IMAGES Ali Cafer Gurbuz, James H. McClellan, Justin Romberg, and Waymond R. Scott, Jr.
- Proceedings in Applied Mathematics and Mechanics, 31 October 2007 Compressive Sampling via Random Convolution
- Randomized Group Testing for Acoustic Source Localization William Mantzele, Justin Romberge, and Karim Sabram
- MULTISCALE WEDGELET IMAGE ANALYSIS: FAST DECOMPOSITIONS AND MODELING
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- Efficient Seismic Forward Modeling using Simultaneous Random Sources and Sparsity R. Neelamani, C. E. Krohn, J. R. Krebs, M. Deffenbaugh, J. E. Anderson, ExxonMobil; and
- SENSING BY RANDOM CONVOLUTION Justin Romberg
- The Dantzig Selector and Generalized Thresholding Justin Romberg
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- Variational Methods for Compressive Sampling Justin Romberga
- IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, VOL. 4, NO. 2, APRIL 2010 421 Dynamic Updating for `1 Minimization
- Sparse Channel Separation using Random Probes Justin Romberg and Ramesh Neelamani
- Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions
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