{"id":"https://openalex.org/W2411229538","doi":"https://doi.org/10.1109/acpr.2015.7486565","title":"Adaptive multi-view clustering via cross trace lasso","display_name":"Adaptive multi-view clustering via cross trace lasso","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2411229538","doi":"https://doi.org/10.1109/acpr.2015.7486565","mag":"2411229538"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2015.7486565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","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/A5100391415","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0001-6853-8278"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dong Wang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112749024","display_name":"Ran He","orcid":"https://orcid.org/0000-0002-3807-991X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran He","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115602506","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0001-5224-8647"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Wang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103202227","display_name":"Tieniu Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tieniu Tan","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100391415"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21880339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"559","last_page":"563"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9969000220298767,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9969000220298767,"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/T10057","display_name":"Face and Expression Recognition","score":0.9940999746322632,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.739058256149292},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.694606602191925},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6243047118186951},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.607803225517273},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5969235897064209},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5769994258880615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4423132538795471},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44203120470046997},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.41470277309417725},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3973666727542877},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3867150545120239},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.323697566986084},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3194839358329773},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21972903609275818}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.739058256149292},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.694606602191925},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6243047118186951},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.607803225517273},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5969235897064209},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5769994258880615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4423132538795471},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44203120470046997},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.41470277309417725},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3973666727542877},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3867150545120239},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.323697566986084},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3194839358329773},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21972903609275818},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acpr.2015.7486565","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","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":23,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W1550614472","https://openalex.org/W1966479305","https://openalex.org/W1991311318","https://openalex.org/W1993962865","https://openalex.org/W2007972815","https://openalex.org/W2085789144","https://openalex.org/W2101324110","https://openalex.org/W2105709960","https://openalex.org/W2121947440","https://openalex.org/W2126337883","https://openalex.org/W2142674578","https://openalex.org/W2154415691","https://openalex.org/W2165644552","https://openalex.org/W2399260173","https://openalex.org/W2405459681","https://openalex.org/W2950602671","https://openalex.org/W6603183647","https://openalex.org/W6675134712","https://openalex.org/W6675968127","https://openalex.org/W6678962389","https://openalex.org/W6682991666","https://openalex.org/W6684671274"],"related_works":["https://openalex.org/W1515021623","https://openalex.org/W3155171010","https://openalex.org/W2119862467","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,74,80,102],"novel":[3],"multi-view":[4,148],"clustering":[5,149],"method":[6,138],"by":[7],"learning":[8],"auto-regression":[9],"problems":[10],"under":[11,40,48,118],"structural":[12],"constraints":[13],"and":[14,51,69,141],"treating":[15],"the":[16,24,31,57,63,70,87,115,129],"regression":[17,71,90,112],"coefficients":[18,91,113],"as":[19],"new":[20],"feature":[21],"representations":[22],"for":[23,114],"cluster":[25],"partition.":[26],"In":[27],"particular,":[28],"we":[29,61,122],"take":[30],"data":[32,39,64,97],"intrinsic":[33],"correlation":[34],"structure":[35],"into":[36,56],"account.":[37],"Correlated":[38],"one":[41,67],"view":[42,50,68,76],"tend":[43],"to":[44,54,78,94,109,127],"be":[45],"also":[46],"related":[47],"another":[49],"are":[52],"likely":[53],"fall":[55],"same":[58,116],"group.":[59],"Therefore":[60],"pair":[62],"matrix":[65],"from":[66,73],"coefficient":[72],"different":[75],"together":[77],"meet":[79],"trace":[81],"Lasso":[82],"constraint,":[83],"which":[84],"adaptively":[85],"adjusts":[86],"sparsity":[88],"of":[89],"in":[92],"order":[93],"promote":[95],"consistent":[96],"correlations":[98],"across":[99],"views.":[100,120],"Then":[101],"joint":[103],"low-rank":[104],"constraint":[105],"is":[106,139],"further":[107],"imposed":[108],"encourage":[110],"similar":[111],"samples":[117],"distinct":[119],"Finally,":[121],"develop":[123],"an":[124],"effective":[125],"algorithm":[126],"optimize":[128],"objective":[130],"function.":[131],"And":[132],"experimental":[133],"results":[134],"demonstrate":[135],"that":[136],"our":[137],"useful":[140],"fairly":[142],"competitive":[143],"compared":[144],"with":[145],"other":[146],"state-of-the-art":[147],"methods.":[150]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}