{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T15:53:45Z","timestamp":1774626825689,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2014,7,12]],"date-time":"2014-07-12T00:00:00Z","timestamp":1405123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100000592","name":"Fulbright Commission","doi-asserted-by":"publisher","award":["91-543"],"award-info":[{"award-number":["91-543"]}],"id":[{"id":"10.13039\/501100000592","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000592","name":"Fulbright Commission","doi-asserted-by":"publisher","award":["DEC-2011\/01\/B\/ST6\/07318"],"award-info":[{"award-number":["DEC-2011\/01\/B\/ST6\/07318"]}],"id":[{"id":"10.13039\/501100000592","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2014,7,12]]},"DOI":"10.1145\/2576768.2598291","type":"proceedings-article","created":{"date-parts":[[2014,7,11]],"date-time":"2014-07-11T12:10:42Z","timestamp":1405080642000},"page":"879-886","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":97,"title":["Multiple regression genetic programming"],"prefix":"10.1145","author":[{"given":"Ignacio","family":"Arnaldo","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, USA"}]},{"given":"Krzysztof","family":"Krawiec","sequence":"additional","affiliation":[{"name":"Poznan University of Technology, Poznan, Poland"}]},{"given":"Una-May","family":"O'Reilly","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA, USA"}]}],"member":"320","published-online":{"date-parts":[[2014,7,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2009.05.016"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/2567709.2502606"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/4235.996017"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1214\/009053604000000067"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1975.1055349"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The elements of statistical learning: data mining, inference and prediction","author":"Hastie T.","year":"2009","unstructured":"T. Hastie , R. Tibshirani , and J. Friedman . The elements of statistical learning: data mining, inference and prediction . Springer , 2 edition, 2009 . T. Hastie, R. Tibshirani, and J. Friedman. The elements of statistical learning: data mining, inference and prediction. Springer, 2 edition, 2009."},{"key":"e_1_3_2_1_7_1","first-page":"64","volume-title":"Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications","author":"Iba H.","year":"1995","unstructured":"H. Iba , T. Sato , and H. de Garis . Numerical genetic programming for system identification. In J. P. Rosca, editor , Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications , pages 64 -- 75 , Tahoe City, California, USA , 9 July 1995 . H. Iba, T. Sato, and H. de Garis. Numerical genetic programming for system identification. In J. P. Rosca, editor, Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications, pages 64--75, Tahoe City, California, USA, 9 July 1995."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/DMISP.1993.248637"},{"key":"e_1_3_2_1_9_1","series-title":"LNCS","first-page":"70","volume-title":"Genetic Programming, Proceedings of EuroGP'2003","author":"Keijzer M.","year":"2003","unstructured":"M. Keijzer . Improving symbolic regression with interval arithmetic and linear scaling . In C. Ryan, T. Soule, M. Keijzer, E. Tsang, R. Poli, and E. Costa, editors, Genetic Programming, Proceedings of EuroGP'2003 , volume 2610 of LNCS , pages 70 -- 82 , Essex, 14--16 Apr. 2003 . Springer-Verlag . M. Keijzer. Improving symbolic regression with interval arithmetic and linear scaling. In C. Ryan, T. Soule, M. Keijzer, E. Tsang, R. Poli, and E. Costa, editors, Genetic Programming, Proceedings of EuroGP'2003, volume 2610 of LNCS, pages 70--82, Essex, 14--16 Apr. 2003. Springer-Verlag."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:GENP.0000030195.77571.f9"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1752-1688.2002.tb00991.x"},{"key":"e_1_3_2_1_12_1","first-page":"1106","volume-title":"Proceedings of the Genetic and Evolutionary Computation Conference","author":"McKay B.","year":"1999","unstructured":"B. McKay , M. Willis , D. Searson , and G. Montague . Non-linear continuum regression using genetic programming . In W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, editors, Proceedings of the Genetic and Evolutionary Computation Conference , volume 2 , pages 1106 -- 1111 , Orlando, Florida, USA , 13--17 July 1999 . Morgan Kaufmann . B. McKay, M. Willis, D. Searson, and G. Montague. Non-linear continuum regression using genetic programming. In W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, editors, Proceedings of the Genetic and Evolutionary Computation Conference, volume 2, pages 1106--1111, Orlando, Florida, USA, 13--17 July 1999. Morgan Kaufmann."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176346150"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.2514\/6.2004-4379"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.camwa.2012.02.049"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1177\/0049124103262064"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2012.03.003"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463372.2463486"},{"key":"e_1_3_2_1_20_1","first-page":"2137","volume-title":"Neural Networks, 2006. IJCNN '06. International Joint Conference on","author":"Xue F.","year":"2006","unstructured":"F. Xue , R. Subbu , and P. Bonissone . Locally weighted fusion of multiple predictive models . In Neural Networks, 2006. IJCNN '06. International Joint Conference on , pages 2137 -- 2143 , 2006 . F. Xue, R. Subbu, and P. Bonissone. Locally weighted fusion of multiple predictive models. In Neural Networks, 2006. IJCNN '06. International Joint Conference on, pages 2137--2143, 2006."}],"event":{"name":"GECCO '14: Genetic and Evolutionary Computation Conference","location":"Vancouver BC Canada","acronym":"GECCO '14","sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"]},"container-title":["Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2576768.2598291","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2576768.2598291","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T07:00:53Z","timestamp":1750230053000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2576768.2598291"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,7,12]]},"references-count":19,"alternative-id":["10.1145\/2576768.2598291","10.1145\/2576768"],"URL":"https:\/\/doi.org\/10.1145\/2576768.2598291","relation":{},"subject":[],"published":{"date-parts":[[2014,7,12]]},"assertion":[{"value":"2014-07-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}