Overcoming graph topology imbalance for inductive and scalable semi-supervised learning

Author:

Dornaika F.,Ibrahim Z.,Bosaghzadeh A.

Funder

Euskal Herriko Unibertsitatea

European Regional Development Fund

Publisher

Elsevier BV

Subject

Software

Reference42 articles.

1. Manifold regularization: A geometric framework for learning from labeled and unlabeled examples;Belkin;J. Mach. Learn. Res.,2006

2. Accelerating flexible manifold embedding for scalable semi-supervised learning;Qiu;IEEE Trans. Circuits Syst. Video Technol.,2019

3. V. Sindhwani, P. Niyogi, Linear manifold regularization for large scale semi-supervised learning, in: Proc. of the 22nd ICML Workshop on Learning with Partially Classified Training Data, 2005.

4. Z. Song, X. Yang, Z. Xu, I. King, Graph-based semi-supervised learning: A comprehensive review, in: IEEE Transactions on Neural Networks and Learning Systems, 2022, pp. 1–21.

5. Parameterless local discriminant embedding;Bosaghzadeh;Neural Process. Lett.,2013

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