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Matrix Decomposition on Graphs: A Functional View

Abstract : We propose a functional view of matrix decomposition problems on graphs such as geometric matrix completion and graph regularized dimensionality reduction. Our unifying framework is based on a key idea that using reduced basis to represent a function on the product space of graph is sufficient to recover a low rank matrix approximation even from a sparse signal. We validate our framework on several real and synthetic benchmarks (for both problems) where it either outperforms state of the art or achieves competitive results at a fraction of the computational effort of prior work.
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https://hal.archives-ouvertes.fr/hal-02871840
Contributor : Abhishek Sharma <>
Submitted on : Friday, October 16, 2020 - 2:56:57 AM
Last modification on : Sunday, October 18, 2020 - 3:30:26 AM

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  • HAL Id : hal-02871840, version 2

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Abhishek Sharma, Maks Ovsjanikov. Matrix Decomposition on Graphs: A Functional View. 2020. ⟨hal-02871840v2⟩

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