DISTRIBUTED ALGORITHM FOR GRAPH SIGNAL INPAINTING

被引：0
|
作者：
Chen, Siheng [1 ,2 ]
Sandryhaila, Aliaksei [3 ]
Kovacevic, Jelena [1 ,2 ,4 ]
机构：
[1] Carnegie Mellon Univ, Dept ECE, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Ctr Bioimage Informat, Pittsburgh, PA 15213 USA
[3] Carnegie Mellon Univ, HP Vert, Pittsburgh, PA 15213 USA
[4] Carnegie Mellon Univ, Dept BME, Pittsburgh, PA 15213 USA
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) | 2015年
基金：
美国国家科学基金会;
关键词：
Signal processing on graphs; graph signal inpainting; distributed computing; REGULARIZATION; FRAMEWORK;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
We present a distributed and decentralized algorithm for graph signal inpainting. The previous work obtained a closed-form solution with matrix inversion. In this paper, we ease the computation by using a distributed algorithm, which solves graph signal inpainting by restricting each node to communicate only with its local nodes. We show that the solution of the distributed algorithm converges to the closed-form solution with the corresponding convergence speed. Experiments on online blog classification and temperature prediction suggest that the convergence speed of the proposed distributed algorithm is competitive with that of the centralized algorithm, especially when a graph tends to be regular. Since a distributed algorithm does not require to collect data to a center, it is more practical and efficient.
引用
收藏
页码：3731 / 3735
页数：5
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