{"id":"https://openalex.org/W1488597662","doi":"https://doi.org/10.1109/icme.2015.7177432","title":"Discriminative multi-view feature selection and fusion","display_name":"Discriminative multi-view feature selection and fusion","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1488597662","doi":"https://doi.org/10.1109/icme.2015.7177432","mag":"1488597662"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2015.7177432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2015.7177432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100630042","display_name":"Yanbin Liu","orcid":"https://orcid.org/0000-0003-4724-8065"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yanbin Liu","raw_affiliation_strings":["School of Computer Science and Technology, Tianjin Universtiy, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tianjin Universtiy, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059871312","display_name":"Binbing Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binbing Liao","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, China","School of Computer Science and Technology, Tianjin Universtiy, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, China","institution_ids":["https://openalex.org/I168879160"]},{"raw_affiliation_string":"School of Computer Science and Technology, Tianjin Universtiy, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031819155","display_name":"Yahong Han","orcid":"https://orcid.org/0000-0003-2768-1398"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yahong Han","raw_affiliation_strings":["School of Computer Science and Technology, Tianjin Universtiy, China","Tianjin Key Laboratory of Cognitive Computing and Application, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Tianjin Universtiy, China","institution_ids":[]},{"raw_affiliation_string":"Tianjin Key Laboratory of Cognitive Computing and Application, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100630042"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7364,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77648616,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"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":0.9939000010490417,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9907000064849854,"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/discriminative-model","display_name":"Discriminative model","score":0.7655409574508667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7370737195014954},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.729079008102417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.723179817199707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.639894962310791},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5065528154373169},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4730638265609741},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.45695212483406067},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4435093402862549},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.443342924118042},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4400861859321594},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4108809530735016},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.2870510220527649},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.06848692893981934}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7655409574508667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7370737195014954},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.729079008102417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.723179817199707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.639894962310791},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5065528154373169},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4730638265609741},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.45695212483406067},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4435093402862549},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.443342924118042},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4400861859321594},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4108809530735016},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2870510220527649},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.06848692893981934},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2015.7177432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2015.7177432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W12820539","https://openalex.org/W18701524","https://openalex.org/W19235576","https://openalex.org/W1871180460","https://openalex.org/W2014788385","https://openalex.org/W2019863495","https://openalex.org/W2023119292","https://openalex.org/W2023221658","https://openalex.org/W2048679005","https://openalex.org/W2050964073","https://openalex.org/W2070753207","https://openalex.org/W2107887685","https://openalex.org/W2137758646","https://openalex.org/W2155803963","https://openalex.org/W2158281641","https://openalex.org/W2166663637","https://openalex.org/W2166782149","https://openalex.org/W2169393274","https://openalex.org/W2171837816","https://openalex.org/W2273758417","https://openalex.org/W2799061466","https://openalex.org/W2950109329","https://openalex.org/W4302161581","https://openalex.org/W4386207016","https://openalex.org/W6676180653","https://openalex.org/W6693932004"],"related_works":["https://openalex.org/W2120164251","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"In":[0,47],"computer":[1],"vision":[2],"tasks":[3],"such":[4],"as":[5],"action":[6,136],"recognition":[7,137],"and":[8,32,38,56,61,119,139,152],"image":[9,142],"classification,":[10],"combining":[11],"multiple":[12,44,66,96],"visual":[13],"feature":[14,45,54,67,71,97,150],"sets":[15],"is":[16,114,124,129],"proven":[17],"to":[18,34],"be":[19],"an":[20],"effective":[21],"strategy.":[22],"However,":[23],"simply":[24],"combing":[25],"these":[26],"features":[27,64],"may":[28],"cause":[29],"high":[30],"dimensionality":[31],"lead":[33],"noises.":[35],"Feature":[36],"selection":[37,55,76,151],"fusion":[39,57],"are":[40],"common":[41],"choices":[42],"for":[43],"representation.":[46],"this":[48],"paper,":[49],"we":[50,73,99],"propose":[51],"a":[52],"multi-view":[53,149],"method":[58],"which":[59],"chooses":[60],"fuses":[62],"discriminative":[63,70],"from":[65],"sets.":[68],"For":[69,95],"selection,":[72],"learn":[74],"the":[75,80,83,107,111,146],"matrix":[77,113,123],"W":[78],"by":[79],"minimization":[81],"of":[82,103,148],"trace":[84],"ratio":[85],"objective":[86],"function":[87],"with":[88],"\u2113":[89],"<sub":[90],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[91],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2,1</sub>":[92],"norm":[93],"regularization.":[94],"fusion,":[98],"incorporate":[100],"local":[101],"structures":[102],"each":[104],"view":[105],"in":[106,116],"Laplacian":[108,112],"matrix.":[109],"Since":[110],"constructed":[115],"unsupervised":[117],"manner":[118],"scaled":[120],"category":[121],"indicator":[122],"solved":[125],"iteratively,":[126],"our":[127],"work":[128],"fully":[130],"unsupervised.":[131],"Experimental":[132],"results":[133],"on":[134],"four":[135],"datasets":[138,144],"two":[140],"large-scale":[141],"classification":[143],"demonstrate":[145],"effectiveness":[147],"fusion.":[153]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}