Galen Reeves

Assistant Professor in the Department of Electrical and Computer Engineering

External address: 
140 Science Dr., 321 Gross Hall, Durham, NC 27708
Phone: 
(919) 668-4042
Webpages: 
Links

LAS DO5: Information Theoretic Measures for Complex and Uncertain Data awarded by North Carolina State University (Principal Investigator). 2015

Data Readiness Level - Task 2.7; Delivery Order 03 awarded by North Carolina State University (Principal Investigator). 2014 to 2015

Data Readiness Level - Mathematical Foundations awarded by North Carolina State University (Principal Investigator). 2013 to 2014

Reeves, G. "The fundamental limits of stable recovery in compressed sensing." IEEE International Symposium on Information Theory - Proceedings (January 1, 2014): 3017-3021. Full Text

Reeves, G, and Donoho, D. "The minimax noise sensitivity in compressed sensing." IEEE International Symposium on Information Theory - Proceedings (December 19, 2013): 116-120. Full Text

Donoho, D, and Reeves, G. "Achieving Bayes MMSE performance in the sparse signal + Gaussian white noise model when the noise level is unknown." IEEE International Symposium on Information Theory - Proceedings (December 19, 2013): 101-105. Full Text

Reeves, G. "Beyond sparsity: Universally stable compressed sensing when the number of 'free' values is less than the number of observations." 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013 (December 1, 2013): 17-20. Full Text

Reeves, G, and Gastpar, MC. "Approximate sparsity pattern recovery: Information-theoretic lower bounds." IEEE Transactions on Information Theory 59.6 (2013): 3451-3465. Full Text

Reeves, G, and Gastpar, M. "The sampling rate-distortion tradeoff for sparsity pattern recovery in compressed sensing." IEEE Transactions on Information Theory 58.5 (2012): 3065-3092. Full Text

Reeves, G, and Gastpar, M. "Compressed sensing phase transitions: Rigorous bounds versus replica predictions." 2012 46th Annual Conference on Information Sciences and Systems, CISS 2012 (2012). Full Text

Donoho, D, and Reeves, G. "The sensitivity of compressed sensing performance to relaxation of sparsity." IEEE International Symposium on Information Theory - Proceedings (2012): 2211-2215. Full Text

Reeves, G, and Gastpar, M. "On the role of diversity in sparsity estimation." IEEE International Symposium on Information Theory - Proceedings (2011): 119-123. Full Text

Reeves, G, Goela, N, Milosavljevic, N, and Gastpar, M. "A compressed sensing wire-tap channel." 2011 IEEE Information Theory Workshop, ITW 2011 (2011): 548-552. Full Text

Pages

Renna, F, Wang, L, Yuan, X, Yang, J, Reeves, G, Calderbank, R, Carin, L, and Rodrigues, MRD. "Classification and Reconstruction of High-Dimensional Signals From Low-Dimensional Features in the Presence of Side Information." November 2016. Full Text

Llull, P, Reeves, G, Carin, L, and Brady, DJ. "Performance assessment of image translation-engineered point spread functions." July 18, 2016. Full Text

Van Den Boom, W, Dunson, D, and Reeves, G. "Quantifying uncertainty in variable selection with arbitrary matrices." January 14, 2016. Full Text

Renna, F, Wang, L, Yuan, X, Yang, J, Reeves, G, Calderbank, R, Carin, L, and Rodrigues, MRD. "Classification and reconstruction of compressed GMM signals with side information." September 28, 2015. Full Text