{"id":"https://openalex.org/W2978971817","doi":"https://doi.org/10.1109/ijcnn.2019.8852076","title":"A Multiple Kernel Machine with Incremental Learning using Sparse Representation","display_name":"A Multiple Kernel Machine with Incremental Learning using Sparse Representation","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978971817","doi":"https://doi.org/10.1109/ijcnn.2019.8852076","mag":"2978971817"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852076","doi":"https://doi.org/10.1109/ijcnn.2019.8852076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852076","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"International Joint Conference on Neural Networks (IJCNN)","issn_l":"2161-4407","issn":["2161-4407"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5028995727","display_name":"Ali Pezeshki","orcid":"https://orcid.org/0000-0002-7142-5685","observed_orcids":["https://orcid.org/0000-0002-7142-5685"]},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Pezeshki","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017501434","display_name":"M.R. Azimi-Sadjadi","orcid":"https://orcid.org/0000-0003-1644-9833","observed_orcids":["https://orcid.org/0000-0003-1644-9833"]},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mahmood R. Azimi-Sadjadi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado","institution_ids":["https://openalex.org/I92446798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022614295","display_name":"Christopher Robbiano","orcid":"https://orcid.org/0000-0003-2758-5435","observed_orcids":["https://orcid.org/0000-0003-2758-5435"]},"institutions":[{"id":"https://openalex.org/I92446798","display_name":"Colorado State University","ror":"https://ror.org/03k1gpj17","country_code":"US","type":"education","lineage":["https://openalex.org/I92446798"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Robbiano","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado","institution_ids":["https://openalex.org/I92446798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I92446798"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.28780001401901245,"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/T12676","display_name":"Machine Learning and ELM","score":0.28780001401901245,"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/T11698","display_name":"Underwater Acoustics Research","score":0.20479999482631683,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.09120000153779984,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/incremental-learning","display_name":"incremental learning","score":0.8420000076293945},{"id":"https://openalex.org/keywords/sparse-representation","display_name":"sparse representation","score":0.9980000257492065},{"id":"https://openalex.org/keywords/pattern-classification","display_name":"pattern classification","score":0.8399999737739563},{"id":"https://openalex.org/keywords/representative-samples","display_name":"representative samples","score":0.6399999856948853},{"id":"https://openalex.org/keywords/underwater-target-classification","display_name":"underwater target classification","score":0.871999979019165},{"id":"https://openalex.org/keywords/sonar-data","display_name":"sonar data","score":0.7680000066757202}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.780843198299408},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6987752914428711},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.6686345338821411},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.6558697819709778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6425715684890747},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.626388430595398},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.5927602648735046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5669640302658081},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.5306262969970703},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5110477209091187},{"id":"https://openalex.org/C55851704","wikidata":"https://www.wikidata.org/wiki/Q7623983","display_name":"String kernel","level":5,"score":0.48753759264945984},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.4756041467189789},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4723690152168274},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36750078201293945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36521434783935547},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852076","doi":"https://doi.org/10.1109/ijcnn.2019.8852076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852076","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"International Joint Conference on Neural Networks (IJCNN)","issn_l":"2161-4407","issn":["2161-4407"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1964168965","https://openalex.org/W1964514974","https://openalex.org/W1986931325","https://openalex.org/W1991359796","https://openalex.org/W2047479285","https://openalex.org/W2062128912","https://openalex.org/W2071325675","https://openalex.org/W2109743529","https://openalex.org/W2114598124","https://openalex.org/W2130988232","https://openalex.org/W2135046866","https://openalex.org/W2140937576","https://openalex.org/W2145295623","https://openalex.org/W2147656689","https://openalex.org/W2151693816","https://openalex.org/W2170356051","https://openalex.org/W2604913466","https://openalex.org/W2747307614","https://openalex.org/W2750479813","https://openalex.org/W2811045405"],"related_works":["https://openalex.org/W7081978853","https://openalex.org/W2107827174","https://openalex.org/W1991359796","https://openalex.org/W4386638237","https://openalex.org/W1989958192","https://openalex.org/W2783388698","https://openalex.org/W4226293505","https://openalex.org/W4412924242","https://openalex.org/W7051460131","https://openalex.org/W238862651"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,26,32,83,109],"new":[4,110],"multiple":[5,36,141],"kernel":[6,37,86,142],"machine":[7,143],"with":[8,88,112],"in-situ":[9],"learning":[10,121],"capability":[11],"is":[12,29,102,123],"introduced":[13],"for":[14,25,61,108,127,153],"pattern":[15,28,47,111],"classification":[16],"using":[17,157],"sparse":[18,68,81,99],"representation":[19,73],"framework.":[20],"A":[21],"vector-valued":[22,76,105],"score":[23,77,106],"function":[24,78,107],"given":[27],"generated":[30],"as":[31],"linear":[33],"combination":[34],"of":[35,40,74,85,130],"functions,":[38],"each":[39],"which":[41,125],"measures":[42],"the":[43,46,52,67,72,75,98,104,131,135],"similarity":[44],"between":[45],"to":[48,79,90],"be":[49,80,117],"classified":[50],"and":[51,147],"representative":[53,59],"samples":[54,60,93],"from":[55,94],"every":[56],"class.":[57],"The":[58,139],"different":[62,95],"classes":[63],"are":[64],"selected":[65],"through":[66],"approximations,":[69],"by":[70],"forcing":[71],"in":[82],"dictionary":[84],"functions":[87],"respect":[89],"all":[91],"data":[92],"classes.":[96],"After":[97],"weight":[100],"matrix":[101],"found,":[103],"unknown":[113],"class":[114],"label":[115],"can":[116],"computed.":[118],"An":[119],"incremental":[120,128],"process":[122],"developed":[124],"allows":[126],"updating":[129],"system":[132],"without":[133],"impacting":[134],"previously":[136],"learnt":[137],"patterns.":[138],"proposed":[140],"was":[144],"then":[145],"implemented":[146],"benchmarked":[148],"against":[149],"other":[150],"multi-kernel":[151],"methods":[152],"classifying":[154],"underwater":[155],"objects":[156],"low":[158],"frequency":[159],"sonar":[160],"data.":[161]},"counts_by_year":[],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2019-10-10T00:00:00"}