1. Chen, B., Wu, H., Mo, W., Chattopadhyay, I., Lipson, H.: Autostacker: a compositional evolutionary learning system. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, 15–19 July 2018, pp. 402–409 (2018)
2. Christ, M., Braun, N., Neuffer, J., Kempa-Liehr, A.W.: Time series feature extraction on basis of scalable hypothesis tests (tsfresh - a python package). Neurocomputing 307, 72–77 (2018)
3. Elsken, T., Metzen, J.H., Hutter, F.: Neural architecture search: a survey. J. Mach. Learn. Res. 20, 55:1–55:21 (2019)
4. Erickson, N., et al.: AutoGluon-tabular: robust and accurate AutoML for structured data. CoRR abs/2003.06505 (2020)
5. Feurer, M., Klein, A., Eggensperger, K., Springenberg, J.T., Blum, M., Hutter, F.: Efficient and robust automated machine learning. In: Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, Montreal, Quebec, Canada, 7–12 December 2015, pp. 2962–2970 (2015)