compendium

S. Chen, A. Sandryhaila, J. M. F. Moura, and J. Kovačević. Signal recovery on graphs: Variation minimization. IEEE Trans. Signal Process., 63(17):460-4624, Sept. 2015.

[ pdf | @ IEEE Xplore | @ arXiv | bibtex]

We consider the problem of signal recovery on graphs. Graphs model data with complex structure as signals on a graph. Graph signal recovery recovers one or multiple smooth graph signals from noisy, corrupted, or incomplete measurements. We formulate graph signal recovery as an optimization problem, for which we provide a general solution through the alternating direction methods of multipliers. We show how signal inpainting, matrix completion, robust principal component analysis, and anomaly detection all relate to graph signal recovery and provide corresponding specific solutions and theoretical analysis. We validate the proposed methods on real-world recovery problems, including online blog classification, bridge condition identification, temperature estimation, recommender system for jokes, and expert opinion combination of online blog classification.

This work is licensed under a Creative Commons GNU General Public License. To view a copy of this license, visit http://creativecommons.org/licenses/GPL/2.0. If you use this code or any part thereof in your research or publication, please also include a reference to this paper. Thank you!

N/A

N/A

N/A

contact

For more information or to report bugs contact jelenak at cmu dot edu.