Parsimony doesn't mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{eurogp07:DeFalco,

• author = "Ivanoe {De Falco} and Antonio {Della Cioppa} and Domenico Maisto and Umberto Scafuri and Ernesto Tarantino",
• title = "Parsimony doesn't mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data",
• editor = "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
• booktitle = "Proceedings of the 10th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "4445",
• year = "2007",
• address = "Valencia, Spain",
• month = "11-13 " # apr,
• pages = "351--360",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-71602-0",
• ISBN = "3-540-71602-5",
• DOI = "doi:10.1007/978-3-540-71605-1_33",
• abstract = "A Genetic Programming algorithm based on Solomonoff probabilistic induction is designed and used to face an Inductive Inference task, i.e., symbolic regression. To this aim, some test functions are dressed with increasing levels of noise and the algorithm is employed to denoise the resulting function and recover the starting functions. Then, the algorithm is compared against a classical parsimony-based GP. The results shows the superiority of the Solomonoff-based approach.",
• notes = "Part of \cite{ebner:2007:GP} EuroGP'2007 held in conjunction with EvoCOP2007, EvoBIO2007 and EvoWorkshops2007",

}

Genetic Programming entries for Ivanoe De Falco Antonio Della Cioppa Domenico Maisto Umberto Scafuri Ernesto Tarantino

Citations