{"id":"https://openalex.org/W2991155877","doi":"https://doi.org/10.1109/pimrc.2019.8904143","title":"Learning to Optimize with Unsupervised Learning: Training Deep Neural Networks for URLLC","display_name":"Learning to Optimize with Unsupervised Learning: Training Deep Neural Networks for URLLC","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2991155877","doi":"https://doi.org/10.1109/pimrc.2019.8904143","mag":"2991155877"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc.2019.8904143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2019.8904143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","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/A5053151490","display_name":"Chengjian Sun","orcid":"https://orcid.org/0000-0002-1733-5005"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengjian Sun","raw_affiliation_strings":["Beihang University,School of Electronics and Information Engineering,Beijing,China","School of Electronics and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Electronics and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082950698","display_name":"Chenyang Yang","orcid":"https://orcid.org/0000-0003-0058-0765"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyang Yang","raw_affiliation_strings":["Beihang University,School of Electronics and Information Engineering,Beijing,China","School of Electronics and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Electronics and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053151490"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":4.9515,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.95770595,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13553","display_name":"Age of Information Optimization","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12131","display_name":"Wireless Signal Modulation Classification","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7740165591239929},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6738535165786743},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5756357908248901},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5719996094703674},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.550318717956543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5412328839302063},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5093863606452942},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5045274496078491},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.44060277938842773},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4237658679485321},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4217706620693207},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42162948846817017},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3742203712463379},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12757456302642822},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08623287081718445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7740165591239929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6738535165786743},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5756357908248901},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5719996094703674},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.550318717956543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5412328839302063},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5093863606452942},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5045274496078491},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.44060277938842773},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4237658679485321},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4217706620693207},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42162948846817017},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3742203712463379},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12757456302642822},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08623287081718445},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc.2019.8904143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2019.8904143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1534416612","https://openalex.org/W1568229137","https://openalex.org/W1689203892","https://openalex.org/W2024013565","https://openalex.org/W2036533317","https://openalex.org/W2109911863","https://openalex.org/W2119213815","https://openalex.org/W2131000650","https://openalex.org/W2137983211","https://openalex.org/W2181303654","https://openalex.org/W2216406802","https://openalex.org/W2594169092","https://openalex.org/W2604924587","https://openalex.org/W2616867685","https://openalex.org/W2617267184","https://openalex.org/W2801937512","https://openalex.org/W2936009584","https://openalex.org/W3103060003","https://openalex.org/W3146803896","https://openalex.org/W4250589301"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W4220926404","https://openalex.org/W3123344745"],"abstract_inverted_index":{"Learning":[0],"the":[1,38,47,63,77,85,88,96,141,148],"optimized":[2],"solution":[3,52,90],"as":[4,95,135],"a":[5,73,126],"function":[6,79],"of":[7,33,66,122],"environmental":[8],"parameters":[9],"by":[10,45,147],"deep":[11,82],"neural":[12],"networks":[13],"(DNN)":[14],"is":[15,93,102],"effective":[16],"in":[17,21,28,130],"solving":[18,46],"numerical":[19],"optimization":[20,48,109,128],"real":[22],"time":[23],"for":[24],"time-sensitive":[25],"resource":[26],"allocation":[27],"wireless":[29],"systems.":[30],"Existing":[31],"works":[32],"learning":[34],"to":[35,61,75,104,117],"optimize":[36,118],"train":[37],"DNN":[39,149],"with":[40,80,111],"labels,":[41],"which":[42,113,138],"are":[43,53,114],"generated":[44],"problems.":[49],"The":[50,100],"learned":[51],"often":[54],"inaccurate":[55],"and":[56,107,120,132],"hence":[57],"cannot":[58],"be":[59,145],"employed":[60],"ensure":[62],"stringent":[64],"quality":[65],"service.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"propose":[72],"framework":[74,101],"learn":[76],"latent":[78],"unsupervised":[81],"learning,":[83],"where":[84],"property":[86],"that":[87,140],"optimal":[89],"should":[91],"satisfy":[92],"used":[94],"\"supervision":[97],"signal\"":[98],"implicitly.":[99],"applicable":[103],"both":[105],"variable":[106,127],"functional":[108],"problems":[110],"constraints,":[112],"respectively":[115],"formulated":[116],"variables":[119],"functions":[121],"concern.":[123],"We":[124],"take":[125],"problem":[129],"ultra-reliable":[131],"low-latency":[133],"communications":[134],"an":[136],"example,":[137],"demonstrates":[139],"ultra-high":[142],"reliability":[143],"can":[144],"supported":[146],"without":[150],"supervision":[151],"labels.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}