@inproceedings{f834c412a77940c9a32bb4dd47b967dc,
title = "MATRIX DECOMPOSITION ON GRAPHS: A SIMPLIFIED FUNCTIONAL VIEW",
abstract = "We propose a simplified functional view of matrix decomposition problems on graphs such as geometric matrix completion. Our unifying framework is based on the key idea that using a reduced basis to represent functions on the product space is sufficient to recover a low rank matrix approximation even from a sparse signal. We validate our framework on several real and synthetic benchmarks where it either outperforms very competitive baselines or achieves competitive results at a fraction of the computational effort of prior work.",
keywords = "Functional Maps, Geometric Matrix Completion, Low Rank Estimators",
author = "Abhishek Sharma and Maks Ovsjanikov",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE; 2022 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2022 ; Conference date: 22-05-2022 Through 27-05-2022",
year = "2022",
month = jan,
day = "1",
doi = "10.1109/ICASSP43922.2022.9746243",
language = "English",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3358--3362",
booktitle = "2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings",
}