{"id":"https://openalex.org/W4388082263","doi":"https://doi.org/10.1109/pimrc56721.2023.10294022","title":"Efficient Compressed Ratio Estimation Using Online Sequential Learning for Edge Computing","display_name":"Efficient Compressed Ratio Estimation Using Online Sequential Learning for Edge Computing","publication_year":2023,"publication_date":"2023-09-05","ids":{"openalex":"https://openalex.org/W4388082263","doi":"https://doi.org/10.1109/pimrc56721.2023.10294022"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc56721.2023.10294022","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/pimrc56721.2023.10294022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 34th 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/A5112144564","display_name":"Hiroki Oikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiroki Oikawa","raw_affiliation_strings":["The University of Tokyo,Graduate School of Interdisciplinary Information Studies,Tokyo,Japan","Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Graduate School of Interdisciplinary Information Studies,Tokyo,Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034634831","display_name":"Hangli Ge","orcid":"https://orcid.org/0000-0001-8025-3013"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hangli Ge","raw_affiliation_strings":["The University of Tokyo,Graduate School of Interdisciplinary Information Studies,Tokyo,Japan","Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Graduate School of Interdisciplinary Information Studies,Tokyo,Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012068346","display_name":"Noboru Koshizuka","orcid":"https://orcid.org/0000-0002-4728-9425"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Noboru Koshizuka","raw_affiliation_strings":["The University of Tokyo,Graduate School of Interdisciplinary Information Studies,Tokyo,Japan","Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Graduate School of Interdisciplinary Information Studies,Tokyo,Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]},{"raw_affiliation_string":"Graduate School of Interdisciplinary Information Studies, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112144564"],"corresponding_institution_ids":["https://openalex.org/I14396692","https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15823756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"65","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9983000159263611,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7235088348388672},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5918598771095276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4641467332839966},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4254641830921173},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.41696077585220337},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3254663348197937},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07206562161445618}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7235088348388672},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5918598771095276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4641467332839966},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4254641830921173},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.41696077585220337},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3254663348197937},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07206562161445618},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc56721.2023.10294022","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/pimrc56721.2023.10294022","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 34th 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":23,"referenced_works":["https://openalex.org/W1997959284","https://openalex.org/W2015606516","https://openalex.org/W2111072639","https://openalex.org/W2156737235","https://openalex.org/W2158054309","https://openalex.org/W2197305145","https://openalex.org/W2416799949","https://openalex.org/W2486202470","https://openalex.org/W2900362930","https://openalex.org/W2902986194","https://openalex.org/W2914440067","https://openalex.org/W2917550189","https://openalex.org/W2950356207","https://openalex.org/W3009120490","https://openalex.org/W3009483609","https://openalex.org/W3015302423","https://openalex.org/W3128973049","https://openalex.org/W4250955649","https://openalex.org/W4298857966","https://openalex.org/W4302570325","https://openalex.org/W6637967152","https://openalex.org/W6683195989","https://openalex.org/W6684205842"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Owing":[0],"to":[1,54,71,116,129],"the":[2,6,23,61,74,78,86,118,139,146,151,173,185],"widespread":[3],"adoption":[4],"of":[5,8,13,26,145],"Internet":[7],"Things,":[9],"a":[10,36,52,69,127],"vast":[11],"amount":[12],"sensor":[14],"information":[15],"is":[16,31,65,68,154],"being":[17],"acquired":[18,79],"in":[19,149],"real":[20],"time.":[21],"Accordingly,":[22],"communication":[24,56],"cost":[25],"data":[27,37,80,131],"from":[28],"edge":[29,45,113,140,164],"devices":[30],"increasing.":[32],"Compressed":[33],"sensing":[34],"(CS),":[35],"compression":[38,63,75,136,152,177,181],"method":[39,53,70,111,148],"that":[40,94,170],"can":[41,95],"be":[42,96],"used":[43],"on":[44,98,138],"devices,":[46,114],"has":[47],"been":[48],"attracting":[49],"attention":[50],"as":[51,117],"reduce":[55],"costs.":[57],"In":[58,103],"CS,":[59],"estimating":[60,133,150],"appropriate":[62,135],"ratio":[64,76,137,153,182],"important.":[66],"There":[67],"adaptively":[72],"estimate":[73],"for":[77,112,163],"using":[81,141],"reinforcement":[82],"learning":[83,123],"(RL).":[84],"However,":[85],"computational":[87],"costs":[88],"associated":[89],"with":[90,159],"existing":[91,186],"RL":[92,110,161],"methods":[93,162],"utilized":[97],"edges":[99],"are":[100],"often":[101],"high.":[102],"this":[104],"study,":[105],"we":[106],"developed":[107],"an":[108,134],"efficient":[109],"referred":[115],"actor\u2013critic":[119],"online":[120],"sequential":[121],"extreme":[122],"machine":[124],"(AC-OSELM),":[125],"and":[126,179],"system":[128],"compress":[130],"by":[132,156],"AC-OSELM.":[142],"The":[143,166],"performance":[144,178],"proposed":[147],"evaluated":[155],"comparing":[157],"it":[158],"other":[160],"devices.":[165],"experimental":[167],"results":[168],"indicate":[169],"AC-OSELM":[171],"demonstrated":[172],"same":[174],"or":[175],"better":[176],"faster":[180],"estimation":[183],"than":[184],"methods.":[187]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}