The Inefficiency of Genetic Programming for Symbolic Regression
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Springer Nature Switzerland
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https://link.springer.com/content/pdf/10.1007/978-3-031-70055-2_17
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2. Bartlett, D.J., Desmond, H.: Marginalised Normal Regression: unbiased curve fitting in the presence of x-errors. Open J. Astrophys. 6, 42 (2023). https://doi.org/10.21105/astro.2309.00948
3. Bartlett, D.J., Desmond, H., Ferreira, P.G.: Exhaustive symbolic regression. IEEE Trans. Evol. Comput. 28, 950–964 (2023)
4. Burlacu, B., Affenzeller, M., Kronberger, G., Kommenda, M.: Online diversity control in symbolic regression via a fast hash-based tree similarity measure. In: 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 2175–2182. IEEE (2019)
5. Lecture Notes in Computer Science;B Burlacu,2020
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