{"id":"https://openalex.org/W2608738262","doi":"https://doi.org/10.1109/icpr.2016.7900173","title":"One-pass online SVM with extremely small space complexity","display_name":"One-pass online SVM with extremely small space complexity","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2608738262","doi":"https://doi.org/10.1109/icpr.2016.7900173","mag":"2608738262"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5000028651","display_name":"Yangwei Liu","orcid":"https://orcid.org/0000-0001-9653-5760"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yangwei Liu","raw_affiliation_strings":["Department of Computer Science and Engineering, State University of New York at Buffalo"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, State University of New York at Buffalo","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006945148","display_name":"Jinhui Xu","orcid":"https://orcid.org/0000-0001-5730-9429"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinhui Xu","raw_affiliation_strings":["Department of Computer Science and Engineering, State University of New York at Buffalo"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, State University of New York at Buffalo","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000028651"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":1.7775,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.90218723,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3482","last_page":"3487"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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/T12676","display_name":"Machine Learning and ELM","score":0.9990000128746033,"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/T10320","display_name":"Neural Networks and Applications","score":0.9966999888420105,"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/support-vector-machine","display_name":"Support vector machine","score":0.7339450716972351},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.664607048034668},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6023987531661987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5104867219924927},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4899865686893463},{"id":"https://openalex.org/keywords/online-algorithm","display_name":"Online algorithm","score":0.47300535440444946},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.46702221035957336},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4451759457588196},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.4179953932762146},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41130945086479187},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.369238018989563},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.21317428350448608}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7339450716972351},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.664607048034668},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6023987531661987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5104867219924927},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4899865686893463},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.47300535440444946},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46702221035957336},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4451759457588196},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.4179953932762146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41130945086479187},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.369238018989563},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.21317428350448608}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7900173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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":34,"referenced_works":["https://openalex.org/W1531947739","https://openalex.org/W1581774316","https://openalex.org/W1588057731","https://openalex.org/W1923046654","https://openalex.org/W1927353355","https://openalex.org/W1970576786","https://openalex.org/W1985142965","https://openalex.org/W2022859179","https://openalex.org/W2027560232","https://openalex.org/W2063958549","https://openalex.org/W2095895508","https://openalex.org/W2103736488","https://openalex.org/W2109706083","https://openalex.org/W2122537498","https://openalex.org/W2135106139","https://openalex.org/W2139759436","https://openalex.org/W2155398148","https://openalex.org/W2160218441","https://openalex.org/W2162302594","https://openalex.org/W2395797879","https://openalex.org/W2963128781","https://openalex.org/W3007818867","https://openalex.org/W3009009611","https://openalex.org/W4239510810","https://openalex.org/W6632157056","https://openalex.org/W6635271509","https://openalex.org/W6640107507","https://openalex.org/W6674478206","https://openalex.org/W6675774749","https://openalex.org/W6680272842","https://openalex.org/W6682590970","https://openalex.org/W6683584131","https://openalex.org/W6712188645","https://openalex.org/W7035737722"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2340870721","https://openalex.org/W2358318464","https://openalex.org/W4389072957","https://openalex.org/W4308943899"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"consider":[4],"the":[5,39,46,58,79,82,89,93,103,130],"problem":[6],"of":[7,18,42,78,81,92,105,124],"training":[8,28,107],"a":[9,16,25,52],"Support":[10],"Vector":[11],"Machine":[12],"(SVM)":[13],"online":[14,27,126],"using":[15],"stream":[17],"data":[19],"in":[20,70,129],"random":[21],"order.":[22],"We":[23],"provide":[24],"fast":[26],"algorithm":[29,50,64,121],"for":[30],"general":[31],"SVM":[32,43],"on":[33,38],"very":[34,110],"large":[35],"datasets.":[36],"Based":[37],"geometric":[40],"interpretation":[41],"known":[44],"as":[45],"polytope":[47],"distance,":[48],"our":[49,63,120],"uses":[51],"gradient":[53],"descent":[54],"procedure":[55],"to":[56],"solve":[57],"problem.":[59],"With":[60],"high":[61,136],"probability":[62],"outputs":[65],"an":[66],"(\u03b5;":[67,85],"\u03b4)-approximation":[68,86],"result":[69],"constant":[71],"time":[72],"and":[73,102],"space,":[74],"which":[75],"is":[76,95,109],"independent":[77],"size":[80],"dataset,":[83],"where":[84],"means":[87],"that":[88,119],"separating":[90],"margin":[91],"classifier":[94],"almost":[96],"optimal":[97],"(with":[98,112],"error":[99,113],"\u2264":[100,114],"\u03b5),":[101],"number":[104],"misclassified":[106],"points":[108],"small":[111],"\u03b4).":[115],"Experimental":[116],"results":[117],"show":[118],"outperforms":[122],"most":[123],"existing":[125],"algorithms,":[127],"especially":[128],"space":[131],"requirement":[132],"aspect,":[133],"while":[134],"maintaining":[135],"accuracy.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}