{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T16:43:42Z","timestamp":1751993022538,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031216855"},{"type":"electronic","value":"9783031216862"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-21686-2_33","type":"book-chapter","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T08:30:15Z","timestamp":1668760215000},"page":"473-487","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Analysis of\u00a0Neutrality of\u00a0AutoML Search Spaces with\u00a0Local Optima Networks"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1103-5383","authenticated-orcid":false,"given":"Matheus C\u00e2ndido","family":"Teixeira","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0349-4494","authenticated-orcid":false,"given":"Gisele Lobo","family":"Pappa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,19]]},"reference":[{"key":"33_CR1","doi-asserted-by":"publisher","unstructured":"Adair, J., Ochoa, G., Malan, K.M.: Local optima networks for continuous fitness landscapes. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 1407\u20131414. ACM, New York (2019). https:\/\/doi.org\/10.1145\/3319619.3326852","DOI":"10.1145\/3319619.3326852"},{"key":"33_CR2","doi-asserted-by":"crossref","unstructured":"Chicano, F., Ochoa, G., Tomassini, M.: Real-like MAX-SAT instances and the landscape structure across the phase transition. In: Proceedings of GECCO, pp. 207\u2013215 (2021)","DOI":"10.1145\/3449639.3459288"},{"key":"33_CR3","doi-asserted-by":"crossref","unstructured":"Cleghorn, C.W., Ochoa, G.: Understanding parameter spaces using local optima networks. In: Proceedings of GECCO Companion, New York, NY, USA, pp. 1657\u20131664 (2021)","DOI":"10.1145\/3449726.3463145"},{"key":"33_CR4","first-page":"2962","volume":"28","author":"M Feurer","year":"2015","unstructured":"Feurer, M., Klein, A., Eggensperger, K., Springenberg, J., Blum, M., Hutter, F.: Efficient and robust automated machine learning. Adv. Neural Inf. Process. Syst. 28, 2962\u20132970 (2015)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"33_CR5","doi-asserted-by":"crossref","unstructured":"Garciarena, U., Santana, R., Mendiburu, A.: Analysis of the complexity of the automatic pipeline generation problem. In: 2018 IEEE Congress on Evolutionary Computation (CEC), pp. 1\u20138. IEEE (2018)","DOI":"10.1109\/CEC.2018.8477662"},{"key":"33_CR6","doi-asserted-by":"publisher","unstructured":"Hutter, F., Kotthoff, L., Vanschoren, J. (eds.): Automated Machine Learning: Methods, Systems, Challenges. Springer, Heidelberg (2018). in press, https:\/\/doi.org\/10.1007\/978-3-030-05318-5. http:\/\/automl.org\/book","DOI":"10.1007\/978-3-030-05318-5"},{"key":"33_CR7","unstructured":"Jones, T., Forrest, S., et al.: Fitness distance correlation as a measure of problem difficulty for genetic algorithms. In: ICGA, vol. 95, pp. 184\u2013192 (1995)"},{"key":"33_CR8","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.ins.2013.04.015","volume":"241","author":"K Malan","year":"2013","unstructured":"Malan, K., Engelbrecht, A.P.: A survey of techniques for characterising fitness landscapes and some possible ways forward. Inf. Sci. 241, 148\u2013163 (2013)","journal-title":"Inf. Sci."},{"key":"33_CR9","doi-asserted-by":"crossref","unstructured":"Nunes, M., Fraga, P.M., Pappa, G.L.: Fitness landscape analysis of graph neural network architecture search spaces. In: Proceedings of GECCO, New York, NY, USA, pp. 876\u2013884 (2021)","DOI":"10.1145\/3449639.3459318"},{"key":"33_CR10","doi-asserted-by":"crossref","unstructured":"Ochoa, G., Chicano, F.: Local optima network analysis for MAX-SAT. In: Proceedings of the GECCO Companion, pp. 1430\u20131437 (2019)","DOI":"10.1145\/3319619.3326855"},{"key":"33_CR11","doi-asserted-by":"crossref","unstructured":"Ochoa, G., Verel, S., Daolio, F., Tomassini, M.: Local optima networks: a new model of combinatorial fitness landscapes, pp. 233\u2013262 (2014)","DOI":"10.1007\/978-3-642-41888-4_9"},{"key":"33_CR12","doi-asserted-by":"crossref","unstructured":"Pimenta, C.G., de S\u00e1, A.G.C., Ochoa, G., Pappa, G.L.: Fitness landscape analysis of automated machine learning search spaces, pp. 114\u2013130 (2020)","DOI":"10.1007\/978-3-030-43680-3_8"},{"key":"33_CR13","doi-asserted-by":"crossref","unstructured":"Pushak, Y., Hoos, H.H.: AutoML loss landscapes (2022)","DOI":"10.1145\/3558774"},{"key":"33_CR14","doi-asserted-by":"crossref","unstructured":"Rakitianskaia, A., Bekker, E., Malan, K.M., Engelbrecht, A.: Analysis of error landscapes in multi-layered neural networks for classification. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 5270\u20135277. IEEE (2016)","DOI":"10.1109\/CEC.2016.7748360"},{"issue":"2\u20133","key":"33_CR15","first-page":"321","volume":"117","author":"CM Reidys","year":"2001","unstructured":"Reidys, C.M., Stadler, P.F.: Neutrality in fitness landscapes. Appl. Math. Comput. 117(2\u20133), 321\u2013350 (2001)","journal-title":"Appl. Math. Comput."},{"key":"33_CR16","series-title":"Emergence, Complexity and Computation","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-642-41888-4_1","volume-title":"Recent Advances in the Theory and Application of Fitness Landscapes","author":"H Richter","year":"2014","unstructured":"Richter, H.: Fitness landscapes: from evolutionary biology to evolutionary computation. In: Richter, H., Engelbrecht, A. (eds.) Recent Advances in the Theory and Application of Fitness Landscapes. ECC, vol. 6, pp. 3\u201331. Springer, Heidelberg (2014). https:\/\/doi.org\/10.1007\/978-3-642-41888-4_1"},{"key":"33_CR17","doi-asserted-by":"crossref","unstructured":"Tari, S., Ochoa, G.: Local search pivoting rules and the landscape global structure. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 278\u2013286 (2021)","DOI":"10.1145\/3449639.3459295"},{"key":"33_CR18","doi-asserted-by":"crossref","unstructured":"Teixeira, M.C., Pappa, G.L.: Understanding AutoML search spaces with local optima networks. In: Genetic and Evolutionary Computation Conference (2022)","DOI":"10.1145\/3512290.3528743"},{"key":"33_CR19","unstructured":"Traor\u00e9, K.R., Camero, A., Zhu, X.X.: Fitness landscape footprint: a framework to compare neural architecture search problems (2021). http:\/\/arxiv.org\/abs\/2111.01584"},{"key":"33_CR20","doi-asserted-by":"crossref","unstructured":"Treimun-Costa, G., Montero, E., Ochoa, G., Rojas-Morales, N.: Modelling parameter configuration spaces with local optima networks. In: Proceedings of GECCO, pp. 751\u2013759 (2020)","DOI":"10.1145\/3377930.3390199"},{"key":"33_CR21","doi-asserted-by":"crossref","unstructured":"V\u00e9rel, S., Daolio, F., Ochoa, G., Tomassini, M.: Local optima networks with escape edges, pp. 49\u201360 (2012)","DOI":"10.1007\/978-3-642-35533-2_5"}],"container-title":["Lecture Notes in Computer Science","Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21686-2_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T17:12:58Z","timestamp":1709831578000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21686-2_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031216855","9783031216862"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21686-2_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"19 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BRACIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazilian Conference on Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Campinas","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazil","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bracis2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www2.sbc.org.br\/bracis2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"JEMS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"225","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"89","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}