David I Shuman
David I Shuman
Associate Professor of Mathematics, Statistics, and Computer Science, Macalester College
Verified email at macalester.edu - Homepage
Cited by
Cited by
The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
DI Shuman, SK Narang, P Frossard, A Ortega, P Vandergheynst
IEEE Signal Processing Magazine 30 (3), 83-98, 2013
Vertex-frequency analysis on graphs
DI Shuman, B Ricaud, P Vandergheynst
Applied and Computational Harmonic Analysis 40 (2), 260-291, 2016
GSPBOX: A toolbox for signal processing on graphs
N Perraudin, J Paratte, D Shuman, L Martin, V Kalofolias, ...
arXiv preprint arXiv:1408.5781, 2014
A multiscale pyramid transform for graph signals
DI Shuman, MJ Faraji, P Vandergheynst
IEEE Transactions on Signal Processing 64 (8), 2119-2134, 2015
Chebyshev polynomial approximation for distributed signal processing
DI Shuman, P Vandergheynst, P Frossard
2011 International Conference on Distributed Computing in Sensor Systems and …, 2011
Spectrum-adapted tight graph wavelet and vertex-frequency frames
DI Shuman, C Wiesmeyr, N Holighaus, P Vandergheynst
IEEE Transactions on Signal Processing 63 (16), 4223-4235, 2015
A windowed graph Fourier transform
DI Shuman, B Ricaud, P Vandergheynst
2012 IEEE Statistical Signal Processing Workshop (SSP), 133-136, 2012
Learning parametric dictionaries for signals on graphs
D Thanou, DI Shuman, P Frossard
IEEE Transactions on Signal Processing 62 (15), 3849-3862, 2014
A wireless soil moisture smart sensor web using physics-based optimal control: Concept and initial demonstrations
M Moghaddam, D Entekhabi, Y Goykhman, K Li, M Liu, A Mahajan, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2010
Distributed signal processing via Chebyshev polynomial approximation
DI Shuman, P Vandergheynst, D Kressner, P Frossard
IEEE Transactions on Signal and Information Processing over Networks 4 (4 …, 2018
UNLocBoX: A MATLAB convex optimization toolbox for proximal-splitting methods
N Perraudin, V Kalofolias, D Shuman, P Vandergheynst
arXiv preprint arXiv:1402.0779, 2014
Global and local uncertainty principles for signals on graphs
N Perraudin, B Ricaud, DI Shuman, P Vandergheynst
APSIPA Transactions on Signal and Information Processing 7, 2018
Optimal sleep scheduling for a wireless sensor network node
D Shuman, M Liu
2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 1337-1341, 2006
Parametric dictionary learning for graph signals
D Thanou, DI Shuman, P Frossard
2013 IEEE Global Conference on Signal and Information Processing, 487-490, 2013
Measurement scheduling for soil moisture sensing: From physical models to optimal control
DI Shuman, A Nayyar, A Mahajan, Y Goykhman, K Li, M Liu, D Teneketzis, ...
Proceedings of the IEEE 98 (11), 1918-1933, 2010
Semi-supervised learning with spectral graph wavelets
DI Shuman, M Faraji, P Vandergheynst
Proceedings of the International Conference on Sampling Theory and …, 2011
Energy-efficient transmission scheduling with strict underflow constraints
DI Shuman, M Liu, OQ Wu
IEEE transactions on information theory 57 (3), 1344-1367, 2011
Scalable -Channel Critically Sampled Filter Banks for Graph Signals
S Li, Y Jin, DI Shuman
IEEE Transactions on Signal Processing 67 (15), 3954-3969, 2019
On the sparsity of wavelet coefficients for signals on graphs
B Ricaud, DI Shuman, P Vandergheynst
Wavelets and Sparsity XV 8858, 88581L, 2013
Energy-efficient transmission scheduling for wireless media streaming with strict underflow constraints
D Shuman, M Liu
2008 6th International Symposium on Modeling and Optimization in Mobile, Ad …, 2008
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