{"id":"https://openalex.org/W2875435464","doi":"https://doi.org/10.1145/3205651.3208763","title":"Genetically-trained deep neural networks","display_name":"Genetically-trained deep neural networks","publication_year":2018,"publication_date":"2018-07-06","ids":{"openalex":"https://openalex.org/W2875435464","doi":"https://doi.org/10.1145/3205651.3208763","mag":"2875435464"},"language":"en","primary_location":{"id":"doi:10.1145/3205651.3208763","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3205651.3208763","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/A5076890359","display_name":"Krzysztof Pawe\u0142czyk","orcid":null},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Krzysztof Pawe\u0142czyk","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086221093","display_name":"Micha\u0142 Kawulok","orcid":"https://orcid.org/0000-0002-3669-5110"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Michal Kawulok","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041796575","display_name":"Jakub Nalepa","orcid":"https://orcid.org/0000-0002-4026-1569"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jakub Nalepa","raw_affiliation_strings":["Silesian University of Technology, Gliwice, Poland"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076890359"],"corresponding_institution_ids":["https://openalex.org/I119004910"],"apc_list":null,"apc_paid":null,"fwci":0.7703,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.81169872,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9986000061035156,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9980000257492065,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9977999925613403,"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/maxima-and-minima","display_name":"Maxima and minima","score":0.8088545799255371},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7298145294189453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6731996536254883},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.6654939651489258},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6491479873657227},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6139806509017944},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6035441756248474},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5745777487754822},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5468239188194275},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4972832500934601},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.47018730640411377},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.46702173352241516},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1239144504070282},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06367537379264832}],"concepts":[{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.8088545799255371},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7298145294189453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6731996536254883},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6654939651489258},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6491479873657227},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6139806509017944},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6035441756248474},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5745777487754822},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5468239188194275},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4972832500934601},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.47018730640411377},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.46702173352241516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1239144504070282},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06367537379264832},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3205651.3208763","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3205651.3208763","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":[{"id":"https://openalex.org/G8830503514","display_name":null,"funder_award_id":"UMO-2017/25/B/ST6/00474","funder_id":"https://openalex.org/F4320322511","funder_display_name":"Narodowe Centrum Nauki"}],"funders":[{"id":"https://openalex.org/F4320322511","display_name":"Narodowe Centrum Nauki","ror":"https://ror.org/03ha2q922"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2294059674","https://openalex.org/W2593744649","https://openalex.org/W2606006859","https://openalex.org/W2726140679","https://openalex.org/W2753772327","https://openalex.org/W2766534271","https://openalex.org/W2778749116"],"related_works":["https://openalex.org/W1535694475","https://openalex.org/W1965562977","https://openalex.org/W2135804779","https://openalex.org/W2093953062","https://openalex.org/W1554143855","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W4315865067","https://openalex.org/W3208304128"],"abstract_inverted_index":{"Deep":[0],"learning":[1,75],"is":[2,27,84],"a":[3,44,69,107],"widely":[4],"explored":[5],"research":[6],"area,":[7],"as":[8,49],"it":[9],"established":[10],"the":[11,14,20,58,78,93,98,111],"state":[12],"of":[13,22,46,57],"art":[15],"in":[16],"many":[17],"fields.":[18],"However,":[19],"effectiveness":[21],"deep":[23],"neural":[24],"networks":[25],"(DNNs)":[26],"affected":[28],"by":[29,73],"several":[30],"factors":[31],"related":[32],"with":[33,53],"their":[34],"training.":[35],"The":[36],"commonly":[37],"used":[38],"gradient-based":[39],"back-propagation":[40],"algorithm":[41,71],"suffers":[42],"from":[43],"number":[45],"shortcomings,":[47],"such":[48],"slow":[50],"convergence,":[51],"difficulties":[52],"escaping":[54],"local":[55],"minima":[56],"search":[59],"space,":[60],"and":[61,92],"vanishing/exploding":[62],"gradients.":[63],"In":[64],"this":[65],"work,":[66],"we":[67],"propose":[68],"genetic":[70],"assisted":[72],"gradient":[74],"to":[76,86],"improve":[77],"DNN":[79,88,100],"training":[80],"process.":[81],"Our":[82],"method":[83,109],"applicable":[85],"any":[87],"architecture":[89],"or":[90],"dataset,":[91],"reported":[94],"experiments":[95],"confirm":[96],"that":[97],"evolved":[99],"models":[101],"consistently":[102],"outperform":[103],"those":[104],"trained":[105],"using":[106],"classical":[108],"within":[110],"same":[112],"time":[113],"budget.":[114]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
