{"id":"https://openalex.org/W4394897048","doi":"https://doi.org/10.1109/tetci.2024.3386833","title":"Graph Structure Learning With Automatic Search of Hyperparameters Based on Genetic Programming","display_name":"Graph Structure Learning With Automatic Search of Hyperparameters Based on Genetic Programming","publication_year":2024,"publication_date":"2024-04-17","ids":{"openalex":"https://openalex.org/W4394897048","doi":"https://doi.org/10.1109/tetci.2024.3386833"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2024.3386833","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2024.3386833","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-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/A5103200054","display_name":"Pengda Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengda Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, Anhui, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103284674","display_name":"Mingjie Lu","orcid":"https://orcid.org/0009-0007-2048-0856"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjie Lu","raw_affiliation_strings":["School of Computer and Control Engineering, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076122416","display_name":"Weiqing Yan","orcid":"https://orcid.org/0000-0001-7869-2404"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqing Yan","raw_affiliation_strings":["School of Computer and Control Engineering, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432277","display_name":"Dong Yang","orcid":"https://orcid.org/0000-0002-9907-395X"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Yang","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061364578","display_name":"Zhaowei Liu","orcid":"https://orcid.org/0000-0003-0179-815X"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaowei Liu","raw_affiliation_strings":["School of Computer and Control Engineering, Yantai University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Control Engineering, Yantai University, Yantai, China","institution_ids":["https://openalex.org/I18452120"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103200054"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":1.3759,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83135573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":"6","first_page":"4155","last_page":"4164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.996999979019165,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.996999979019165,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9832000136375427,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.958299994468689,"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/hyperparameter","display_name":"Hyperparameter","score":0.727733850479126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6324062943458557},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5813239812850952},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.5567356944084167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4812193214893341},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45938968658447266},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33689647912979126}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.727733850479126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6324062943458557},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5813239812850952},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.5567356944084167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4812193214893341},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45938968658447266},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33689647912979126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2024.3386833","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2024.3386833","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G496790220","display_name":null,"funder_award_id":"62272405","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1662382123","https://openalex.org/W1990184714","https://openalex.org/W2949208225","https://openalex.org/W2964015378","https://openalex.org/W2970183009","https://openalex.org/W2984323660","https://openalex.org/W2997591727","https://openalex.org/W3004946360","https://openalex.org/W3005644236","https://openalex.org/W3012644407","https://openalex.org/W3012918605","https://openalex.org/W3068123808","https://openalex.org/W3081203761","https://openalex.org/W3101709902","https://openalex.org/W3102969158","https://openalex.org/W3117805350","https://openalex.org/W3118642024","https://openalex.org/W3121087702","https://openalex.org/W3126138172","https://openalex.org/W3153206160","https://openalex.org/W3163591408","https://openalex.org/W3172335055","https://openalex.org/W3173737612","https://openalex.org/W3174318304","https://openalex.org/W3174320978","https://openalex.org/W3175164304","https://openalex.org/W3176294187","https://openalex.org/W3201829457","https://openalex.org/W4214813463","https://openalex.org/W4221143762","https://openalex.org/W4287282757","https://openalex.org/W4287726895","https://openalex.org/W4289389616","https://openalex.org/W4297733535","https://openalex.org/W4317624859","https://openalex.org/W4320481815","https://openalex.org/W4384832026","https://openalex.org/W4385687011","https://openalex.org/W4387731535","https://openalex.org/W4390939347","https://openalex.org/W4394862809","https://openalex.org/W6637178625","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6748856961","https://openalex.org/W6760886919","https://openalex.org/W6771621015","https://openalex.org/W6779462361","https://openalex.org/W6780489652","https://openalex.org/W6840343660","https://openalex.org/W6841058540"],"related_works":["https://openalex.org/W2602382373","https://openalex.org/W3003615511","https://openalex.org/W4285827128","https://openalex.org/W3198113463","https://openalex.org/W2787698406","https://openalex.org/W2963844355","https://openalex.org/W4361251046","https://openalex.org/W3095116576","https://openalex.org/W98577079","https://openalex.org/W4301772239"],"abstract_inverted_index":{"Graph":[0],"neural":[1],"networks":[2],"(GNNs)":[3],"rely":[4],"heavily":[5],"on":[6,170],"graph":[7,27,49,57,81,90,100,108,138],"structures":[8,58,109],"and":[9,16,33,110,124,140,174],"artificial":[10],"hyperparameters,":[11],"which":[12,36],"may":[13],"increase":[14,162],"computation":[15],"affect":[17,69],"performance.":[18,42],"Most":[19],"GNNs":[20],"use":[21],"original":[22,26],"graphs,":[23],"but":[24,102],"the":[25,70,73,88,99,104,117,122,137,152,161],"data":[28],"has":[29,167],"problems":[30],"with":[31,146],"noise":[32],"incomplete":[34],"information,":[35],"easily":[37],"leads":[38],"to":[39,55,132,176],"poor":[40],"GNN":[41,74],"For":[43],"this":[44,94],"kind":[45],"of":[46,64,72,136,154],"problem,":[47],"recent":[48],"structure":[50,82,91,101,139],"learning":[51,83,92],"methods":[52],"consider":[53],"how":[54],"generate":[56],"containing":[59],"label":[60],"information.":[61],"The":[62],"settings":[63],"some":[65],"hyperparameters":[66,112],"will":[67],"also":[68,103],"expression":[71],"model.":[75],"This":[76],"paper":[77,95],"proposes":[78],"a":[79],"genetic":[80],"method":[84],"(Genetic-GSL).":[85],"Different":[86],"from":[87],"existing":[89],"methods,":[93,148],"not":[96],"only":[97],"optimizes":[98],"hyperparameters.":[105,141],"Specifically,":[106],"different":[107,111],"are":[113,119,128],"used":[114],"as":[115],"parents;":[116,123],"offspring":[118,127],"cross-mutated":[120],"through":[121,130],"then":[125],"excellent":[126],"selected":[129],"evaluation":[131],"achieve":[133],"dynamic":[134],"fitting":[135],"Experiments":[142],"show":[143],"that,":[144],"compared":[145],"other":[147],"Genetic-GSL":[149,166],"basically":[150],"improves":[151],"performance":[153,169],"node":[155,171],"classification":[156,172],"tasks":[157,173],"by":[158],"1.2%.":[159],"With":[160],"in":[163],"evolution":[164],"algebra,":[165],"good":[168],"resistance":[175],"adversarial":[177],"attacks.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
