{"id":"https://openalex.org/W2903072120","doi":"https://doi.org/10.1109/icpr.2018.8545594","title":"Robust Adaptive Label Propagation by Double Matrix Decomposition","display_name":"Robust Adaptive Label Propagation by Double Matrix Decomposition","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2903072120","doi":"https://doi.org/10.1109/icpr.2018.8545594","mag":"2903072120"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th 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/A5100356958","display_name":"Huan Zhang","orcid":"https://orcid.org/0000-0002-3698-5409"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huan Zhang","raw_affiliation_strings":["School of Computer Science and Technolog, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technolog, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100423029","display_name":"Zhao Zhang","orcid":"https://orcid.org/0000-0002-5703-7969"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Zhang","raw_affiliation_strings":["School of Computer Science and Technolog, Soochow University, Suzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technolog, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359839","display_name":"Sheng Li","orcid":"https://orcid.org/0000-0003-1205-8632"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheng Li","raw_affiliation_strings":["Adobc Research, Adobe Systems Inc, San Jose, California, United States"],"affiliations":[{"raw_affiliation_string":"Adobc Research, Adobe Systems Inc, San Jose, California, United States","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039671101","display_name":"Qiaolin Ye","orcid":"https://orcid.org/0000-0002-8793-8610"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiaolin Ye","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Naniing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Naniing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061195038","display_name":"Mingbo Zhao","orcid":"https://orcid.org/0000-0003-0381-4360"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Mingbo Zhao","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100377147","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0002-3094-7735"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Wang","raw_affiliation_strings":["School of Computer and Information Science, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100356958"],"corresponding_institution_ids":["https://openalex.org/I3923682"],"apc_list":null,"apc_paid":null,"fwci":0.9772,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8249304,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2160","last_page":"2165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9945999979972839,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9945999979972839,"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/T10057","display_name":"Face and Expression Recognition","score":0.9901999831199646,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9638000130653381,"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":0.644484281539917},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5734607577323914},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5477317571640015},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5175199508666992},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5047394037246704},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4975586235523224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4896102547645569},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35787713527679443},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.06927227973937988}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.644484281539917},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5734607577323914},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5477317571640015},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5175199508666992},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5047394037246704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4975586235523224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4896102547645569},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35787713527679443},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.06927227973937988},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1154172097","https://openalex.org/W1510147702","https://openalex.org/W1969198379","https://openalex.org/W2006793117","https://openalex.org/W2050754297","https://openalex.org/W2053186076","https://openalex.org/W2071778287","https://openalex.org/W2076363162","https://openalex.org/W2089939542","https://openalex.org/W2132709984","https://openalex.org/W2139823104","https://openalex.org/W2154455818","https://openalex.org/W2277747675","https://openalex.org/W2296425695","https://openalex.org/W2343830850","https://openalex.org/W2480248159","https://openalex.org/W2514846838","https://openalex.org/W2744216160","https://openalex.org/W2755136704","https://openalex.org/W2759831793","https://openalex.org/W2768975974","https://openalex.org/W2994340921","https://openalex.org/W3100040694","https://openalex.org/W6635552349","https://openalex.org/W6663149272","https://openalex.org/W6673087439","https://openalex.org/W6680434193","https://openalex.org/W6682494755","https://openalex.org/W6742773263"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4254199101","https://openalex.org/W4224009465","https://openalex.org/W1670153145","https://openalex.org/W4306674287","https://openalex.org/W4236907339","https://openalex.org/W4300427796","https://openalex.org/W4286629047","https://openalex.org/W4287196534","https://openalex.org/W2051864124"],"abstract_inverted_index":{"In":[0,130],"this":[1],"paper,":[2],"we":[3],"investigate":[4],"the":[5,27,41,49,58,67,74,80,84,98,116,121,140,145,150,159,163,173,196],"robust":[6,153],"transductive":[7,34],"label":[8,35,46,55,77,101,107,118,124,154,197],"prediction":[9,47,78,155,198],"problem.":[10],"Technically,":[11],"a":[12,104,110,135],"Robust":[13],"Adaptive":[14],"Label":[15],"Propagation":[16],"framework":[17],"by":[18,44],"Double":[19],"Matrix":[20],"Decomposition,":[21],"called":[22],"ALP-MD,":[23],"is":[24],"proposed":[25],"for":[26,79,126,188],"semi-supervised":[28],"data":[29,51,165],"classification.":[30,129],"Compared":[31],"with":[32],"existing":[33],"propagation":[36],"models,":[37],"our":[38,63,94,168],"ALP-MD":[39,64,95,132,169],"improves":[40],"classification":[42],"power":[43],"performing":[45],"in":[48,142,162],"clean":[50,54,105,122,164],"space":[52,56],"and":[53,91,109,113,156,183,191,193],"at":[57],"same":[59],"time.":[60],"More":[61],"specifically,":[62],"clearly":[65],"integrates":[66,144],"idea":[68],"of":[69,76,152],"double":[70],"matrix":[71,102,108,125],"decomposition":[72],"into":[73,103,149],"process":[75,151],"noise":[81,90,111,141],"removal.":[82],"Since":[83],"predicted":[85,99],"soft":[86,100,106,123],"labels":[87],"usually":[88],"contains":[89],"mixed":[92],"signs,":[93],"explicitly":[96,171],"decomposes":[97],"term":[112,137],"then":[114],"estimates":[115],"hard":[117],"based":[119],"on":[120],"more":[127],"accurate":[128],"addition,":[131],"also":[133],"involves":[134],"regularization":[136],"to":[138,176,184],"model":[139],"data,":[143],"adaptive":[146],"weights":[147,160,175],"learning":[148,161],"moreover":[157],"performs":[158],"space.":[166],"Thus,":[167],"can":[170],"ensure":[172],"learned":[174],"be":[177,185],"informative":[178],"as":[179,181],"much":[180],"possible":[182],"joint":[186],"optimal":[187],"both":[189],"representation":[190],"classification,":[192],"potentially":[194],"enhance":[195],"ability.":[199],"Extensive":[200],"comparisons":[201],"demonstrated":[202],"its":[203],"effectiveness.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
