{"id":"https://openalex.org/W4293731247","doi":"https://doi.org/10.1109/tpami.2022.3202565","title":"Kernel-Based Generalized Median Computation for Consensus Learning","display_name":"Kernel-Based Generalized Median Computation for Consensus Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4293731247","doi":"https://doi.org/10.1109/tpami.2022.3202565","pmid":"https://pubmed.ncbi.nlm.nih.gov/36037458"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3202565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3202565","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2209.10208","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064665597","display_name":"Andreas Nienk\u00f6tter","orcid":"https://orcid.org/0000-0002-7884-2836"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Andreas Nienkotter","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022183918","display_name":"Xiaoyi Jiang","orcid":"https://orcid.org/0000-0001-7678-9528"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoyi Jiang","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064665597"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1388,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54727386,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"45","issue":"5","first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9948999881744385,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9948999881744385,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9842000007629395,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9835000038146973,"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/kernel","display_name":"Kernel (algebra)","score":0.7439373731613159},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.717293918132782},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5732526779174805},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5051293969154358},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.48765480518341064},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4145164489746094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40540000796318054},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3784499168395996},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3726445436477661},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34855616092681885},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2921369969844818},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.16110241413116455}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7439373731613159},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.717293918132782},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5732526779174805},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5051293969154358},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.48765480518341064},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4145164489746094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40540000796318054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3784499168395996},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3726445436477661},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34855616092681885},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2921369969844818},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.16110241413116455}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tpami.2022.3202565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3202565","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:36037458","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36037458","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 pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:2209.10208","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.10208","pdf_url":"https://arxiv.org/pdf/2209.10208","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:zenodo.org:7065731","is_oa":true,"landing_page_url":"https://doi.org/10.1109/TPAMI.2022.3202565","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2209.10208","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.10208","pdf_url":"https://arxiv.org/pdf/2209.10208","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1050024180","display_name":null,"funder_award_id":"CRC 1450","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G1544407157","display_name":null,"funder_award_id":"431460824","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G2689612763","display_name":null,"funder_award_id":"Marie","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4956428346","display_name":null,"funder_award_id":"Horizon 2020 research and innovatio","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5036817778","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innov","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5106512922","display_name":null,"funder_award_id":"Deutsche Forschungsgemeinschaft (DFG","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G5910565596","display_name":"Environmentally efficient full profile drilling solution","funder_award_id":"778602","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6024419964","display_name":null,"funder_award_id":"Deutsche Forschungsgemeinschaft (DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G6052429835","display_name":null,"funder_award_id":"(DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8318064016","display_name":null,"funder_award_id":"Horizon","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8633428685","display_name":null,"funder_award_id":"European Union's Horizon 2020 research and innovat","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W81184795","https://openalex.org/W261725549","https://openalex.org/W938539187","https://openalex.org/W1491527630","https://openalex.org/W1510073064","https://openalex.org/W1587670653","https://openalex.org/W1602075893","https://openalex.org/W1850059000","https://openalex.org/W1967116906","https://openalex.org/W1969792798","https://openalex.org/W1970615687","https://openalex.org/W1986007546","https://openalex.org/W2001642763","https://openalex.org/W2002360418","https://openalex.org/W2002767255","https://openalex.org/W2012090438","https://openalex.org/W2013011196","https://openalex.org/W2017980367","https://openalex.org/W2019180701","https://openalex.org/W2021178514","https://openalex.org/W2025549250","https://openalex.org/W2033079010","https://openalex.org/W2036413831","https://openalex.org/W2037288520","https://openalex.org/W2040751791","https://openalex.org/W2045456727","https://openalex.org/W2046114185","https://openalex.org/W2048901266","https://openalex.org/W2055764977","https://openalex.org/W2068532248","https://openalex.org/W2075241504","https://openalex.org/W2077787678","https://openalex.org/W2078313470","https://openalex.org/W2097827365","https://openalex.org/W2105068202","https://openalex.org/W2107425660","https://openalex.org/W2109181422","https://openalex.org/W2116925220","https://openalex.org/W2129971280","https://openalex.org/W2131479089","https://openalex.org/W2148000173","https://openalex.org/W2157656721","https://openalex.org/W2161669108","https://openalex.org/W2309460698","https://openalex.org/W2475296195","https://openalex.org/W2546774630","https://openalex.org/W2605432550","https://openalex.org/W2619266022","https://openalex.org/W2740248650","https://openalex.org/W2762355386","https://openalex.org/W2776454016","https://openalex.org/W2782029065","https://openalex.org/W2791146007","https://openalex.org/W2912068403","https://openalex.org/W2917412503","https://openalex.org/W2964030756","https://openalex.org/W3000408165","https://openalex.org/W3120740533","https://openalex.org/W4248598408","https://openalex.org/W4252684946","https://openalex.org/W4287819709","https://openalex.org/W4360754846","https://openalex.org/W6676236601","https://openalex.org/W6680062394","https://openalex.org/W6680320696","https://openalex.org/W6683291568","https://openalex.org/W6753415029","https://openalex.org/W6760005058","https://openalex.org/W6762791162","https://openalex.org/W6775415071"],"related_works":["https://openalex.org/W2089892314","https://openalex.org/W1603091392","https://openalex.org/W4386075310","https://openalex.org/W2169565408","https://openalex.org/W2127229869","https://openalex.org/W3123056048","https://openalex.org/W2150638158","https://openalex.org/W2121506664","https://openalex.org/W2363184354","https://openalex.org/W2137862631"],"abstract_inverted_index":{"Computing":[0],"a":[1,5,11,47,75,124],"consensus":[2],"object":[3,79],"from":[4,202],"set":[6],"of":[7,67,78,156,188,194],"given":[8],"objects":[9,45,117,145,167],"is":[10,23,130,168,205],"core":[12],"problem":[13,30,54,85],"in":[14,55,105,150,172,176],"machine":[15],"learning":[16],"and":[17,40,58,93,136,146,184,219],"pattern":[18],"recognition.":[19],"One":[20],"popular":[21],"approach":[22],"to":[24,74,132,209,213],"formulate":[25],"it":[26],"as":[27],"an":[28,157,177],"optimization":[29],"using":[31,181],"the":[32,38,51,63,82,106,113,142,154,163,215],"generalized":[33,52,83,126,148,189,216],"median.":[34],"Previous":[35],"methods":[36,43,69,102],"like":[37],"Prototype":[39],"Distance-Preserving":[41],"Embedding":[42],"transform":[44,60],"into":[46,62],"vector":[48,179],"space,":[49,57,152],"solve":[50],"median":[53,84,127,149,190,217],"this":[56,120],"inversely":[59],"back":[61],"original":[64],"space.":[65],"Both":[66],"these":[68],"have":[70],"been":[71],"successfully":[72],"applied":[73],"wide":[76],"range":[77],"domains,":[80],"where":[81],"has":[86],"inherent":[87],"high":[88],"computational":[89],"complexity":[90],"(typically":[91],"NP-hard)":[92],"therefore":[94],"approximate":[95],"solutions":[96],"are":[97],"required.":[98],"Previously,":[99],"explicit":[100,158,178],"embedding":[101],"were":[103],"used":[104],"computation,":[107],"which":[108],"often":[109],"do":[110],"not":[111],"reflect":[112],"spatial":[114,164],"relationship":[115,143,165],"between":[116,144,166],"exactly.":[118],"In":[119],"work":[121,204],"we":[122],"introduce":[123],"kernel-based":[125],"framework":[128,140],"that":[129,162],"applicable":[131],"both":[133],"positive":[134],"definite":[135],"indefinite":[137],"kernels.":[138],"This":[139],"computes":[141],"its":[147],"kernel":[151,173],"without":[153],"need":[155],"embedding.":[159],"We":[160],"show":[161],"more":[169],"accurately":[170],"represented":[171],"space":[174,180],"than":[175],"easy-to-compute":[182],"kernels,":[183],"demonstrate":[185],"superior":[186],"performance":[187],"computation":[191,218],"on":[192],"datasets":[193],"three":[195],"different":[196],"domains.":[197],"A":[198],"software":[199],"toolbox":[200],"resulting":[201],"our":[203],"made":[206],"publicly":[207],"available":[208],"encourage":[210],"other":[211],"researchers":[212],"explore":[214],"applications.":[220]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}