@inproceedings{c982d8faa8eb46fbb2967428f04a4147,
title = "Signal inpainting on graphs via total variation minimization",
abstract = "We propose a novel recovery algorithm for signals with complex, irregular structure that is commonly represented by graphs. Our approach is a generalization of the signal inpainting technique from classical signal processing. We formulate corresponding minimization problems and demonstrate that in many cases they have closed-form solutions. We discuss a relation of the proposed approach to regression, provide an upper bound on the error for our algorithm and compare the proposed technique with other existing algorithms on real-world datasets.",
keywords = "Signal processing on graphs, semi-supervised learning, signal in-painting, total variation",
author = "Siheng Chen and Aliaksei Sandryhaila and George Lederman and Zihao Wang and Moura, {Jos{\'e} M.F.} and Piervincenzo Rizzo and Jacobo Bielak and Garrett, {James H.} and Jelena Kova{\v c}evi{\'c}",
year = "2014",
doi = "10.1109/ICASSP.2014.6855213",
language = "English (US)",
isbn = "9781479928927",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "8267--8271",
booktitle = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014",
note = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 ; Conference date: 04-05-2014 Through 09-05-2014",
}