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A Statistical Learning Perspective of Genetic Programming.

, , , , , and . EuroGP, volume 5481 of Lecture Notes in Computer Science, page 327-338. Springer, (2009)

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Optimizing coverage of simulated driving scenarios for the autonomous vehicle., , , and . ICCVE, page 1-5. IEEE, (2019)Editorial Introduction.. Evol. Comput., (2009)Universal Consistency and Bloat in GP Some theoretical considerations about Genetic Programming from a Statistical Learning Theory viewpoint., , , and . Rev. d'Intelligence Artif., 20 (6): 805-827 (2006)JEO: Java Evolving Objects., , , , , and . GECCO, page 991-994. Morgan Kaufmann, (2002)A statistical learning theory approach of bloat., , , and . GECCO, page 1783-1784. ACM, (2005)Individual GP: an Alternative Viewpoint for the Resolution of Complex Problems., , , and . GECCO, page 974-981. Morgan Kaufmann, (1999)Introducing machine learning for power system operation support., , , , and . CoRR, (2017)Bio-inspired approaches to anomaly and intrusion detection., and . GECCO (Companion), page 1121-1137. ACM, (2018)A Dynamic Lattice to Evolve Hierarchically Shared Subroutines., , and . EuroGP, volume 1391 of Lecture Notes in Computer Science, page 220-232. Springer, (1998)An Induction-based Control for Genetic Algorithms (Extended Abstract)., , and . ECML, volume 912 of Lecture Notes in Computer Science, page 351-355. Springer, (1995)