{"id":"https://openalex.org/W2914992593","doi":"https://doi.org/10.1109/coginfocom.2018.8639877","title":"The Spiral Discovery Network as an Evolutionary Model for Gradient-Free Non-Convex Optimization","display_name":"The Spiral Discovery Network as an Evolutionary Model for Gradient-Free Non-Convex Optimization","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2914992593","doi":"https://doi.org/10.1109/coginfocom.2018.8639877","mag":"2914992593"},"language":"en","primary_location":{"id":"doi:10.1109/coginfocom.2018.8639877","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginfocom.2018.8639877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","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/A5005893331","display_name":"\u00c1d\u00e1m Csap\u00f3","orcid":"https://orcid.org/0000-0001-9885-137X"},"institutions":[{"id":"https://openalex.org/I83579964","display_name":"Sz\u00e9chenyi Istv\u00e1n University","ror":"https://ror.org/04091f946","country_code":"HU","type":"education","lineage":["https://openalex.org/I83579964"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Adam B. Csapo","raw_affiliation_strings":["Dept. of Informatics, Sz\u00e9chenyi Istv\u00e1n University, Gy\u0151r, Hungary"],"affiliations":[{"raw_affiliation_string":"Dept. of Informatics, Sz\u00e9chenyi Istv\u00e1n University, Gy\u0151r, Hungary","institution_ids":["https://openalex.org/I83579964"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5005893331"],"corresponding_institution_ids":["https://openalex.org/I83579964"],"apc_list":null,"apc_paid":null,"fwci":0.1672,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53167719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"15","issue":null,"first_page":"000347","last_page":"000352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13382","display_name":"Robotics and Automated Systems","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9865999817848206,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7470008134841919},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5212412476539612},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.5020151138305664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49704864621162415},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4459458589553833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43579763174057007},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4354325830936432},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41149812936782837},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.28525954484939575},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0881919264793396}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7470008134841919},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5212412476539612},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.5020151138305664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49704864621162415},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4459458589553833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43579763174057007},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4354325830936432},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41149812936782837},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28525954484939575},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0881919264793396},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coginfocom.2018.8639877","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginfocom.2018.8639877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","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":25,"referenced_works":["https://openalex.org/W1490690518","https://openalex.org/W1971415293","https://openalex.org/W1993953473","https://openalex.org/W2045031658","https://openalex.org/W2076063813","https://openalex.org/W2082222199","https://openalex.org/W2096388912","https://openalex.org/W2146444479","https://openalex.org/W2151019861","https://openalex.org/W2275841169","https://openalex.org/W2400844080","https://openalex.org/W2568880839","https://openalex.org/W2571515229","https://openalex.org/W2757305067","https://openalex.org/W2785976655","https://openalex.org/W2787522646","https://openalex.org/W2794105361","https://openalex.org/W2899771611","https://openalex.org/W4213052256","https://openalex.org/W4232982293","https://openalex.org/W4247645337","https://openalex.org/W4248928965","https://openalex.org/W6756040250","https://openalex.org/W6808801245","https://openalex.org/W7002104625"],"related_works":["https://openalex.org/W2289718384","https://openalex.org/W1995675544","https://openalex.org/W2509524819","https://openalex.org/W2012121796","https://openalex.org/W2068427817","https://openalex.org/W2952090425","https://openalex.org/W2538333368","https://openalex.org/W3127866798","https://openalex.org/W4294845631","https://openalex.org/W1518153952"],"abstract_inverted_index":{"The":[0,52],"Spiral":[1,63],"Discovery":[2,64],"Method":[3],"(SDM)":[4],"was":[5],"originally":[6],"designed":[7],"as":[8,62],"a":[9],"cognitive":[10],"artifact":[11],"to":[12,33,61,76,134],"help":[13],"manage":[14],"the":[15,36,82,85,105,112,127,136,141],"complexities":[16],"of":[17,38,84,107,114,140],"manually":[18],"tuning":[19],"parametric":[20,24],"models":[21,66,95],"in":[22,80,132],"high-dimensional":[23],"spaces.":[25],"Recently,":[26],"several":[27],"modifications":[28],"and":[29,98,138],"enhancements":[30,57],"were":[31],"proposed":[32],"SDM":[34],"with":[35,104],"goal":[37,106],"making":[39,108],"it":[40],"suitable":[41],"for":[42,111],"tasks":[43],"requiring":[44],"automated":[45],"non-convex":[46],"optimization":[47,113],"besides":[48],"manual":[49],"parameter":[50],"configuration.":[51],"key":[53],"challenge":[54],"behind":[55,93],"such":[56],"-":[58,73],"collectively":[59],"referred":[60],"Network":[65],"(SDNs)":[67],"based":[68],"on":[69,126],"their":[70,99],"network-based":[71],"formulation":[72],"is":[74,101],"how":[75],"replace":[77],"human":[78],"intuition":[79],"maintaining":[81],"adaptivity":[83],"search":[86],"process.":[87],"In":[88],"this":[89],"paper,":[90],"recent":[91],"advances":[92],"SDN":[94],"are":[96,130],"summarized,":[97],"theory":[100],"further":[102],"developed":[103],"them":[109],"useful":[110],"multi-level,":[115],"hierarchical":[116],"architectures.":[117],"Results":[118],"from":[119],"experiments":[120],"directed":[121],"at":[122],"optimizing":[123],"convolutional":[124],"networks":[125],"MNIST":[128],"dataset":[129],"presented":[131],"order":[133],"highlight":[135],"strengths":[137],"weaknesses":[139],"approach.":[142]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
