Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms

Author:

Kostovska AnaORCID,Vermetten DiederickORCID,Džeroski SašoORCID,Panov PančeORCID,Eftimov TomeORCID,Doerr CarolaORCID

Publisher

Springer Nature Switzerland

Reference20 articles.

1. Studies in Computational Intelligence;V Basto-Fernandes,2017

2. Chen, X., Jia, S., Xiang, Y.: A review: Knowledge reasoning over knowledge graph. Expert Syst. Appl. 141, 112948 (2020)

3. Costabello, L., Pai, S., Le Van, C., McGrath, R., McCarthy, N., Tabacof, P.: Ampligraph: a library for representation learning on knowledge graphs (2019). Accessed 10 Oct 2019

4. Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the AISTATS. JMLR Workshop and Conference Proceedings, pp. 249–256 (2010)

5. Gruber, T.: Toward principles for the design of ontologies used for knowledge sharing? Int. J. Hum Comput Stud. 43(5–6), 907–928 (1995)

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1. Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks;2024 IEEE Congress on Evolutionary Computation (CEC);2024-06-30

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