{"id":"https://openalex.org/W4401215160","doi":"https://doi.org/10.1145/3638530.3654379","title":"Analysis of Pruned Deep Models Trained with Neuroevolution","display_name":"Analysis of Pruned Deep Models Trained with Neuroevolution","publication_year":2024,"publication_date":"2024-07-14","ids":{"openalex":"https://openalex.org/W4401215160","doi":"https://doi.org/10.1145/3638530.3654379"},"language":"en","primary_location":{"id":"doi:10.1145/3638530.3654379","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638530.3654379","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073046118","display_name":"Federico Da Rold","orcid":"https://orcid.org/0009-0007-7336-5202"},"institutions":[{"id":"https://openalex.org/I26120043","display_name":"Ochanomizu University","ror":"https://ror.org/03599d813","country_code":"JP","type":"education","lineage":["https://openalex.org/I26120043"]},{"id":"https://openalex.org/I4210094952","display_name":"Cross Compass (Japan)","ror":"https://ror.org/00naatv40","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210094952"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Federico Da Rold","raw_affiliation_strings":["Cross Labs, Cross Compass ltd., Kyoto, Japan","Ochanomizu University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0009-0007-7336-5202","affiliations":[{"raw_affiliation_string":"Cross Labs, Cross Compass ltd., Kyoto, Japan","institution_ids":["https://openalex.org/I4210094952"]},{"raw_affiliation_string":"Ochanomizu University, Tokyo, Japan","institution_ids":["https://openalex.org/I26120043"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022001331","display_name":"L\u00e9o Cazenille","orcid":"https://orcid.org/0000-0002-5893-9761"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I4210094488","display_name":"Laboratoire Interdisciplinaire des \u00c9nergies de Demain","ror":"https://ror.org/00m43ek07","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I204730241","https://openalex.org/I4210094488","https://openalex.org/I4210150854"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Leo Cazenille","raw_affiliation_strings":["CNRS, LIED UMR 8236, Paris, France","Universit\u00e9 Paris Cit\u00e9, Paris, France"],"raw_orcid":"https://orcid.org/0000-0002-5893-9761","affiliations":[{"raw_affiliation_string":"CNRS, LIED UMR 8236, Paris, France","institution_ids":["https://openalex.org/I4210094488","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Universit\u00e9 Paris Cit\u00e9, Paris, France","institution_ids":["https://openalex.org/I204730241"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002767684","display_name":"Nathana\u00ebl Aubert-Kato","orcid":"https://orcid.org/0000-0002-9100-1855"},"institutions":[{"id":"https://openalex.org/I26120043","display_name":"Ochanomizu University","ror":"https://ror.org/03599d813","country_code":"JP","type":"education","lineage":["https://openalex.org/I26120043"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nathanael Aubert-Kato","raw_affiliation_strings":["Ochanomizu University, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9100-1855","affiliations":[{"raw_affiliation_string":"Ochanomizu University, Tokyo, Japan","institution_ids":["https://openalex.org/I26120043"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08165997,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"591","last_page":"594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/neuroevolution","display_name":"Neuroevolution","score":0.8885930776596069},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6877334117889404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6143589615821838},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40116578340530396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3367967903614044}],"concepts":[{"id":"https://openalex.org/C118070581","wikidata":"https://www.wikidata.org/wiki/Q2060528","display_name":"Neuroevolution","level":3,"score":0.8885930776596069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6877334117889404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6143589615821838},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40116578340530396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3367967903614044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3638530.3654379","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638530.3654379","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1786044565","https://openalex.org/W1971421925","https://openalex.org/W2131681506","https://openalex.org/W2794698050","https://openalex.org/W2962687375","https://openalex.org/W2985106077","https://openalex.org/W3021119228","https://openalex.org/W3099768174","https://openalex.org/W3106528330","https://openalex.org/W4235571646","https://openalex.org/W4287828539","https://openalex.org/W4391054901","https://openalex.org/W6774302960"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Deep":[0],"neural":[1,36,80],"networks":[2],"show":[3,141],"remarkable":[4],"results":[5],"in":[6,16,23,79,148],"several":[7],"fields":[8],"of":[9,74,77,144,155,172],"machine":[10],"intelligence,":[11],"such":[12,28],"as":[13],"effective":[14],"classification":[15],"computer":[17],"vision":[18],"and":[19,43,108,146,152,168],"robust":[20],"adaptive":[21],"systems":[22],"reinforcement":[24,119],"learning":[25,114,120],"scenarios.":[26],"However,":[27,70],"models":[29,81],"are":[30],"typically":[31],"overparametrized,":[32],"leading":[33],"to":[34,66,92,103,111],"redundant":[35],"pathways":[37],"that":[38],"massively":[39],"increase":[40],"the":[41,56,75,113,135,139,142,149,153,170],"computational":[42],"energetic":[44],"costs":[45],"without":[46],"providing":[47],"any":[48],"significant":[49],"performance":[50],"gain.":[51],"Recent":[52],"works":[53],"have":[54],"addressed":[55],"problem":[57],"by":[58,123],"proposing":[59],"pruning":[60,78,130,173],"techniques":[61],"or":[62],"using":[63],"gradient-free":[64],"neuroevolution":[65],"minimize":[67],"model":[68],"size.":[69],"a":[71,124,129,163],"systematic":[72],"analysis":[73,110,140],"effects":[76],"during":[82],"evolution":[83],"is":[84,132],"still":[85],"missing.":[86],"We":[87,116],"propose":[88],"an":[89],"exploratory":[90,159],"approach":[91,127],"fill":[93],"this":[94],"gap,":[95],"relying":[96],"on":[97,118],"mathematical":[98],"tools":[99],"from":[100,138],"network":[101,105,156],"science":[102],"capture":[104],"structure":[106],"regularities":[107],"information-theoretic":[109],"describe":[112],"process.":[115],"focus":[117],"problems":[121],"solved":[122],"quality":[125],"diversity":[126],"evolving":[128],"operator":[131],"evolved":[133],"along":[134],"models.":[136],"Results":[137],"emergence":[143],"patterns":[145],"regimes":[147],"mutual":[150],"information":[151],"estimation":[154],"measures.":[157],"This":[158],"work":[160],"will":[161],"provide":[162],"solid":[164],"ground":[165],"for":[166],"guiding":[167],"facilitating":[169],"development":[171],"algorithms.":[174]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
