A Consistent Diffusion-Based Algorithm for Semi-Supervised Graph Learning

Author:

Bonald Thomas,De Lara Nathan

Publisher

Springer Nature Switzerland

Reference14 articles.

1. Airoldi, E.M., Blei, D.M., Fienberg, S.E., Xing, E.P.: Mixed membership stochastic blockmodels. J. Mach. Learn. Res. (2008)

2. Berberidis, D., Nikolakopoulos, A.N., Giannakis, G.B.: Adadif: Adaptive diffusions for efficient semi-supervised learning over graphs. In: International Conference on Big Data. IEEE (2018)

3. Chung, F.R.: Spectral graph theory. American Mathematical Soc. (1997)

4. Donnat, C., Zitnik, M., Hallac, D., Leskovec, J.: Learning structural node embeddings via diffusion wavelets. In: International Conference on Knowledge Discovery & Data Mining. In: ACM (2018)

5. Kondor, R.I., Lafferty, J.: Diffusion kernels on graphs and other discrete structures. In: Proceedings of the 19th international conference on machine learning (2002)

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