{"id":"https://openalex.org/W4377715968","doi":"https://doi.org/10.1109/tnnls.2023.3236479","title":"Learning With Incremental Instances and Features","display_name":"Learning With Incremental Instances and Features","publication_year":2023,"publication_date":"2023-05-23","ids":{"openalex":"https://openalex.org/W4377715968","doi":"https://doi.org/10.1109/tnnls.2023.3236479","pmid":"https://pubmed.ncbi.nlm.nih.gov/37220049"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3236479","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3236479","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/A5102025884","display_name":"Shilin Gu","orcid":"https://orcid.org/0000-0003-1681-5856"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shilin Gu","raw_affiliation_strings":["College of Science, National University of Defense Technology, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"College of Science, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003563112","display_name":"Yuhua Qian","orcid":"https://orcid.org/0000-0001-6772-4247"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhua Qian","raw_affiliation_strings":["Institute of Big Data Science and Industry, Shanxi University, Taiyuan, Shanxi, China"],"affiliations":[{"raw_affiliation_string":"Institute of Big Data Science and Industry, Shanxi University, Taiyuan, Shanxi, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091529433","display_name":"Chenping Hou","orcid":"https://orcid.org/0000-0002-9335-0469"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenping Hou","raw_affiliation_strings":["College of Science, National University of Defense Technology, Changsha, Hunan, China"],"affiliations":[{"raw_affiliation_string":"College of Science, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102025884"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":1.049,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80625856,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"35","issue":"7","first_page":"9713","last_page":"9727"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998000264167786,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9998000264167786,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9921000003814697,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9884999990463257,"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":0.8234333992004395},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7907651662826538},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5595725774765015},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5479769706726074},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.544303297996521},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4876912832260132},{"id":"https://openalex.org/keywords/data-space","display_name":"Data space","score":0.4637700915336609},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.45459747314453125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45031076669692993},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.42921534180641174},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.41574063897132874},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3843913972377777},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34418508410453796},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09143620729446411}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234333992004395},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7907651662826538},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5595725774765015},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5479769706726074},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.544303297996521},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4876912832260132},{"id":"https://openalex.org/C2988382989","wikidata":"https://www.wikidata.org/wiki/Q370685","display_name":"Data space","level":2,"score":0.4637700915336609},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.45459747314453125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45031076669692993},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.42921534180641174},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.41574063897132874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3843913972377777},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34418508410453796},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09143620729446411},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3236479","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3236479","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:37220049","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37220049","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":[],"awards":[{"id":"https://openalex.org/G4173930408","display_name":null,"funder_award_id":"61922087","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7031182729","display_name":null,"funder_award_id":"62006238","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7694957091","display_name":null,"funder_award_id":"61906201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1612277053","https://openalex.org/W1878852850","https://openalex.org/W1973678258","https://openalex.org/W1993014433","https://openalex.org/W2012243161","https://openalex.org/W2040870580","https://openalex.org/W2073148270","https://openalex.org/W2095895508","https://openalex.org/W2124101897","https://openalex.org/W2132087961","https://openalex.org/W2150621701","https://openalex.org/W2153338628","https://openalex.org/W2153635508","https://openalex.org/W2346780474","https://openalex.org/W2406838509","https://openalex.org/W2408432900","https://openalex.org/W2441489703","https://openalex.org/W2508718575","https://openalex.org/W2521689864","https://openalex.org/W2594639291","https://openalex.org/W2606980484","https://openalex.org/W2741352581","https://openalex.org/W2784522433","https://openalex.org/W2791769216","https://openalex.org/W2941870464","https://openalex.org/W2949481348","https://openalex.org/W2963311299","https://openalex.org/W2963830375","https://openalex.org/W2965718579","https://openalex.org/W3007092794","https://openalex.org/W3009009611","https://openalex.org/W3016344614","https://openalex.org/W3092051759","https://openalex.org/W3100535899","https://openalex.org/W3159243351","https://openalex.org/W3177001585","https://openalex.org/W4210769749","https://openalex.org/W4229706427","https://openalex.org/W4249572517","https://openalex.org/W6629510986","https://openalex.org/W6639167513","https://openalex.org/W6640107507","https://openalex.org/W6674478206","https://openalex.org/W6675774749","https://openalex.org/W6677768686","https://openalex.org/W6681723013","https://openalex.org/W6683584131","https://openalex.org/W6714150371","https://openalex.org/W6727181731","https://openalex.org/W6729522193","https://openalex.org/W6733923534","https://openalex.org/W6738526744","https://openalex.org/W6738958213","https://openalex.org/W6739308774","https://openalex.org/W6761696168","https://openalex.org/W6779590080","https://openalex.org/W6781155865"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W4361801939","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W2802243998","https://openalex.org/W1521014365"],"abstract_inverted_index":{"In":[0,81],"many":[1],"real-world":[2],"applications,":[3],"data":[4,31,42,53,79,97,122,133],"may":[5],"dynamically":[6],"expand":[7],"over":[8],"time":[9],"in":[10,21,37],"both":[11],"volume":[12,33],"and":[13,34,69,104,139,202],"feature":[14,50,126],"dimensions.":[15],"Besides,":[16],"they":[17],"are":[18],"often":[19],"collected":[20],"batches":[22],"(also":[23],"called":[24,99],"blocks).":[25],"We":[26,107],"refer":[27],"this":[28,82,187],"kind":[29],"of":[30,52,71,155,176,208],"whose":[32],"features":[35,105],"increase":[36],"blocks":[38],"as":[39],"blocky":[40,77,95],"trapezoidal":[41,78,96],"streams.":[43,80],"Current":[44],"works":[45],"either":[46],"assume":[47],"that":[48,59,116],"the":[49,60,76,132,141,152,174,180,196,206],"space":[51],"streams":[54,134],"is":[55],"fixed":[56],"or":[57],"stipulate":[58],"algorithm":[61,88],"receives":[62],"only":[63],"one":[64],"instance":[65],"at":[66],"a":[67,86,91,162],"time,":[68],"none":[70],"them":[72],"can":[73,117],"effectively":[74],"handle":[75],"article,":[83],"we":[84,129,160,172,191],"propose":[85],"novel":[87],"to":[89,109,150,167,178,185],"learn":[90,118],"classification":[92,182],"model":[93,113],"from":[94,119],"streams,":[98],"learning":[100],"with":[101,123],"incremental":[102],"instances":[103],"(IIF).":[106],"attempt":[108],"design":[110],"highly":[111],"dynamic":[112],"update":[114],"strategies":[115],"increasing":[120],"training":[121],"an":[124],"expanding":[125],"space.":[127],"Specifically,":[128],"first":[130],"divide":[131],"obtained":[135],"on":[136],"each":[137,158],"round":[138],"construct":[140],"corresponding":[142],"classifiers":[143],"for":[144],"these":[145],"different":[146],"divided":[147],"parts.":[148],"Then,":[149],"realize":[151],"effective":[153],"interaction":[154],"information":[156],"between":[157],"classifier,":[159],"utilize":[161],"single":[163],"global":[164],"loss":[165],"function":[166],"capture":[168],"their":[169],"relationship.":[170],"Finally,":[171],"use":[173],"idea":[175],"ensemble":[177],"achieve":[179],"final":[181],"model.":[183],"Furthermore,":[184],"make":[186],"method":[188],"more":[189],"applicable,":[190],"directly":[192],"transform":[193],"it":[194],"into":[195],"kernel":[197],"method.":[198],"Both":[199],"theoretical":[200],"analysis":[201,204],"empirical":[203],"validate":[205],"effectiveness":[207],"our":[209],"algorithm.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
