{"id":"https://openalex.org/W2805174380","doi":"https://doi.org/10.1145/3109761.3158392","title":"Field support vector machines","display_name":"Field support vector machines","publication_year":2017,"publication_date":"2017-10-17","ids":{"openalex":"https://openalex.org/W2805174380","doi":"https://doi.org/10.1145/3109761.3158392","mag":"2805174380"},"language":"en","primary_location":{"id":"doi:10.1145/3109761.3158392","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3109761.3158392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st International Conference on Internet of Things and Machine Learning","raw_type":"proceedings-article"},"type":"conference-paper","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/A5026022035","display_name":"Kaizhu Huang","orcid":"https://orcid.org/0000-0002-3034-9639"},"institutions":[{"id":"https://openalex.org/I69356397","display_name":"Xi\u2019an Jiaotong-Liverpool University","ror":"https://ror.org/03zmrmn05","country_code":"CN","type":"education","lineage":["https://openalex.org/I69356397"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaizhu Huang","raw_affiliation_strings":["Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I69356397"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004875127","display_name":"Haochuan Jiang","orcid":"https://orcid.org/0000-0002-8727-4121"},"institutions":[{"id":"https://openalex.org/I69356397","display_name":"Xi\u2019an Jiaotong-Liverpool University","ror":"https://ror.org/03zmrmn05","country_code":"CN","type":"education","lineage":["https://openalex.org/I69356397"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haochuan Jiang","raw_affiliation_strings":["Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I69356397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082548671","display_name":"Xu-Yao Zhang","orcid":"https://orcid.org/0000-0001-9260-188X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu-Yao Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, P.R.China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7164,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.84561679,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9962000250816345,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9921000003814697,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8654061555862427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6921376585960388},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6439113616943359},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6064465641975403},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5216946005821228},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4891970157623291},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.4683346748352051},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45314133167266846},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4368557035923004},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43309056758880615},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3757745027542114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25992104411125183}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8654061555862427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6921376585960388},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6439113616943359},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6064465641975403},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5216946005821228},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4891970157623291},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.4683346748352051},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45314133167266846},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4368557035923004},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43309056758880615},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3757745027542114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25992104411125183},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3109761.3158392","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3109761.3158392","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st International Conference on Internet of Things and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1510526001","https://openalex.org/W1564049492","https://openalex.org/W1618905105","https://openalex.org/W2040193698","https://openalex.org/W2106115875","https://openalex.org/W2106125148","https://openalex.org/W2108598243","https://openalex.org/W2119015427","https://openalex.org/W2119821739","https://openalex.org/W2143104527","https://openalex.org/W2150100034","https://openalex.org/W2153635508","https://openalex.org/W2156338447","https://openalex.org/W2163605009","https://openalex.org/W2170653751","https://openalex.org/W2172000360","https://openalex.org/W2183341477","https://openalex.org/W2342611082","https://openalex.org/W2949117887","https://openalex.org/W3011284156","https://openalex.org/W4240177776"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W1617617605","https://openalex.org/W1487808658"],"abstract_inverted_index":{"The":[0,103],"identically":[1],"and":[2,60,85,123,170],"independently":[3],"distributed":[4],"(i.i.d.)":[5],"condition":[6],"required":[7,117],"by":[8,79,118,139],"conventional":[9,120],"machine":[10],"learning":[11,122],"approaches":[12],"may":[13],"sometimes":[14],"be":[15],"violated":[16],"when":[17],"patterns":[18,65,109],"occur":[19],"as":[20],"groups":[21],"(where":[22],"each":[23,92,146],"group":[24,63,93],"shares":[25],"a":[26,30,47,62,67],"homogeneous":[27],"style,":[28],"called":[29],"field).":[31],"By":[32],"breaking":[33],"it,":[34],"we":[35],"extend":[36],"in":[37,56,98,145,191],"this":[38],"paper":[39],"the":[40,58,74,83,86,99,106,114,119,133,142,148,157,168,174,177,184],"famous":[41],"Support":[42,52],"Vector":[43,53],"Machine":[44,54],"(SVM)":[45],"to":[46,110,154,166],"novel":[48],"framework":[49],"named":[50],"Field":[51],"(F-SVM),":[55],"which":[57],"training":[59],"predicting":[61],"of":[64,94,162,176],"(i.e.,":[66],"field":[68],"pattern)":[69],"are":[70,164],"performed":[71],"simultaneously.":[72],"Specifically,":[73],"proposed":[75,149,185],"F-SVM":[76,150,178,186],"is":[77,129,152],"learned":[78],"optimizing":[80],"simultaneously":[81],"both":[82],"classifier":[84],"Style":[87],"Normalization":[88],"Transformation":[89],"(SNT)":[90],"for":[91],"data,":[95],"even":[96],"feasible":[97],"high-dimensional":[100],"kernel":[101],"space.":[102],"SNT":[104],"transform":[105],"original":[107],"style-discriminative":[108],"style-free":[111],"ones,":[112],"satisfying":[113],"i.i.d.":[115],"assumption":[116],"SVM":[121],"implementation.":[124],"An":[125],"efficient":[126],"optimization":[127],"algorithm":[128],"further":[130],"developed":[131],"with":[132],"convergence":[134],"guaranteed":[135],"theoretically.":[136],"More":[137],"importantly,":[138],"appropriately":[140],"exploring":[141],"style":[143],"consistency":[144],"field,":[147],"model":[151],"able":[153],"significantly":[155],"improve":[156],"classification":[158],"accuracy.":[159],"A":[160],"series":[161],"experiments":[163],"conducted":[165],"verify":[167],"effectiveness":[169],"confirmed":[171],"improvement":[172],"on":[173],"performance":[175],"model.":[179],"Empirical":[180],"results":[181],"show":[182],"that":[183],"outperforms":[187],"other":[188],"relevant":[189],"baselines":[190],"two":[192],"different":[193],"benchmark":[194],"data":[195],"sets.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
