1. Abou-Moustafa, K., Szepesvári, C.: An exponential efron-stein inequality for $$l_q$$ stable learning rules. In: Garivier, A., Kale, S. (eds.) Proceedings of the 30th International Conference on Algorithmic Learning Theory. Proceedings of Machine Learning Research, vol. 98, pp. 31–63 (2019)
2. Anthony, M., Holden, S.B.: Cross-validation for binary classification by real-valued functions: theoretical analysis. In: Proceedings of the Eleventh Annual Conference on Computational Learning Theory, pp. 218–229 (1998)
3. Arlot, S.: V-fold cross-validation improved: V-fold penalization. 40 pages, plus a separate technical appendix (2008)
4. Arlot, S., Celisse, A.: A survey of cross-validation procedures for model selection. Stat. Surv. 4, 40–79 (2010)
5. Arlot, S., Lerasle, M.: Choice of v for v-fold cross-validation in least-squares density estimation. J. Mach. Learn. Res. 17(208), 1–50 (2016)