A survey of signal processing based graph learning techniques

Subbareddy, B and Reddy, P Charantej and Siripuram, Aditya and Zhang, Jingxin (2019) A survey of signal processing based graph learning techniques. In: 1st International Conference on Industrial Artificial Intelligence, IAI, 22-26 July 2019, Shenyang, China.

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Abstract

Recent advances in technology have led to easy data acquisition mechanisms in many fields, leading to massive datasets. It is often of interest to understand the inherent structure and learn the best representation of the given dataset. Graphs are a powerful way to model interrelationships between data features-well constructed meaningful graphs help in representing and processing the data effectively. The graph topology needs to be inferred from the observed data. In this survey, we briefly explore signal processing based graph learning approaches that have been proposed in the literature and propose new research directions.

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IITH Creators:	IITH Creators ORCiD Siripuram, Aditya UNSPECIFIED
Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Graph learning, Graph signal processing, Network topology inference, Sparse signal processing, Indexed in Scopus
Subjects:	Electrical Engineering
Divisions:	Department of Electrical Engineering
Depositing User:	Team Library
Date Deposited:	28 Oct 2019 06:38
Last Modified:	28 Oct 2019 06:38
URI:	http://raiithold.iith.ac.in/id/eprint/6861
Publisher URL:	http://doi.org/10.1109/ICIAI.2019.8850827
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