Learning Label Initialization for Time-Dependent Harmonic Extension
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Abstract (arXiv)
Node classification on graphs can be formulated as the Dirichlet problem on graphs where the signal is given at the labeled nodes, and the harmonic extension is done on the unlabeled nodes. This paper considers a time-dependent version of the Dirichlet problem on graphs and shows how to improve its solution by learning the proper initialization vector on the unlabeled nodes. Further, we show that the improved solution is at par with state-of-the-art methods used for node classification. Finally, we conclude this paper by discussing the importance of parameter t, pros, and future directions.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 23 of its 48 references that are in the map. First posted on arXiv 3 May 2022.
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23 of 48 references.
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11 more
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