{"id":"https://openalex.org/W4307090379","doi":"https://doi.org/10.1109/tnnls.2022.3212390","title":"Distributed Estimation of Support Vector Machines for Matrix Data","display_name":"Distributed Estimation of Support Vector Machines for Matrix Data","publication_year":2022,"publication_date":"2022-11-03","ids":{"openalex":"https://openalex.org/W4307090379","doi":"https://doi.org/10.1109/tnnls.2022.3212390","pmid":"https://pubmed.ncbi.nlm.nih.gov/36269928"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3212390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3212390","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101990262","display_name":"Wangli Xu","orcid":"https://orcid.org/0000-0002-5657-0884"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wangli Xu","raw_affiliation_strings":["Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China","School of Statistics, Center for Applied Statistics, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"School of Statistics, Center for Applied Statistics, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100327238","display_name":"Jiamin Liu","orcid":"https://orcid.org/0009-0009-5979-0856"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiamin Liu","raw_affiliation_strings":["School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069315147","display_name":"Heng Lian","orcid":"https://orcid.org/0000-0002-6008-6614"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Heng Lian","raw_affiliation_strings":["Department of Mathematics, City University of Hong Kong, Kowloon Tong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101990262"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":1.5696,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.84009212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"35","issue":"5","first_page":"6643","last_page":"6653"},"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":0.9850999712944031,"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":0.9850999712944031,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9660999774932861,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.8236405849456787},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7425923943519592},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.7140592336654663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6626282334327698},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.6388590335845947},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.574648380279541},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.46929246187210083},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43697723746299744},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42818671464920044},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3475475013256073},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3441486954689026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2579598128795624},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16391921043395996}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8236405849456787},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7425923943519592},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.7140592336654663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6626282334327698},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.6388590335845947},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.574648380279541},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.46929246187210083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43697723746299744},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42818671464920044},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3475475013256073},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3441486954689026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2579598128795624},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16391921043395996},{"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3212390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3212390","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:36269928","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36269928","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6100000143051147}],"awards":[{"id":"https://openalex.org/G3974516973","display_name":null,"funder_award_id":"11300721","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G5878997773","display_name":null,"funder_award_id":"11971478","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6529044653","display_name":null,"funder_award_id":"Z200001","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G6990293604","display_name":null,"funder_award_id":"11300519","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G8080196064","display_name":null,"funder_award_id":"11871411","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8658710022","display_name":null,"funder_award_id":"11301718","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G8714140063","display_name":null,"funder_award_id":"11311822","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W648260396","https://openalex.org/W1506806321","https://openalex.org/W1564947197","https://openalex.org/W1975041748","https://openalex.org/W1989851442","https://openalex.org/W2003585400","https://openalex.org/W2010353172","https://openalex.org/W2012159277","https://openalex.org/W2123696247","https://openalex.org/W2150382423","https://openalex.org/W2156909104","https://openalex.org/W2170121562","https://openalex.org/W2586353914","https://openalex.org/W2613645387","https://openalex.org/W2807787126","https://openalex.org/W2940902102","https://openalex.org/W2962769133","https://openalex.org/W2964231067","https://openalex.org/W2964291083","https://openalex.org/W2971170030","https://openalex.org/W3005774088","https://openalex.org/W3093031590","https://openalex.org/W3099978158","https://openalex.org/W3117526597","https://openalex.org/W3117771886","https://openalex.org/W3127889425","https://openalex.org/W3184654024","https://openalex.org/W3211421771","https://openalex.org/W4205970259","https://openalex.org/W4206966243","https://openalex.org/W4239510810","https://openalex.org/W4292025355","https://openalex.org/W6679490728","https://openalex.org/W6684952376","https://openalex.org/W6696581697","https://openalex.org/W6733227126","https://openalex.org/W6752434656","https://openalex.org/W6757145712","https://openalex.org/W6797032914","https://openalex.org/W6928833312"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W2090763504","https://openalex.org/W4385769873","https://openalex.org/W2015759683","https://openalex.org/W4281634296","https://openalex.org/W4319161863","https://openalex.org/W2359063982","https://openalex.org/W2360658320"],"abstract_inverted_index":{"Discrimination":[0],"problems":[1],"are":[2],"of":[3,35,50,79],"significant":[4],"interest":[5,15],"in":[6,16,44,53],"the":[7,32,36,47,51,54,59,71,77,80],"machine":[8,20],"learning":[9,21],"literature.":[10],"There":[11],"has":[12],"been":[13],"growing":[14],"extending":[17],"traditional":[18],"vector-based":[19],"techniques":[22],"to":[23],"their":[24],"matrix":[25],"forms.":[26],"In":[27],"this":[28],"article,":[29],"we":[30,63],"investigate":[31],"statistical":[33],"properties":[34],"nuclear-norm-based":[37],"regularized":[38],"linear":[39],"support":[40],"vector":[41],"machines":[42],"(SVMs),":[43],"particular":[45],"establishing":[46],"convergence":[48,73],"rate":[49],"estimator":[52,67],"high-dimensional":[55],"setting.":[56],"Furthermore,":[57],"within":[58],"distributed":[60],"estimation":[61],"paradigm,":[62],"propose":[64],"a":[65],"communication-efficient":[66],"that":[68],"can":[69],"achieve":[70],"same":[72],"rate.":[74],"We":[75],"illustrate":[76],"performances":[78],"estimators":[81],"via":[82],"some":[83],"simulation":[84],"examples":[85],"and":[86],"an":[87],"empirical":[88],"data":[89],"analysis.":[90]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
