{"id":"https://openalex.org/W4408355367","doi":"https://doi.org/10.1109/icassp49660.2025.10890486","title":"Multi-view Subspace Classification: A Hierarchical Contrastive Approach and Low-rank Latent Representation","display_name":"Multi-view Subspace Classification: A Hierarchical Contrastive Approach and Low-rank Latent Representation","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408355367","doi":"https://doi.org/10.1109/icassp49660.2025.10890486"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10890486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5044423719","display_name":"Deyu Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deyu Zeng","raw_affiliation_strings":["Shenzhen University,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053974811","display_name":"Tengyu Zhang","orcid":"https://orcid.org/0009-0007-5929-3310"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tengyu Zhang","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004392249","display_name":"Zongze Wu","orcid":"https://orcid.org/0000-0002-0597-1426"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongze Wu","raw_affiliation_strings":["Shenzhen University,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763568","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0001-6351-9019"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Wuhan University,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102823200","display_name":"Chris Ding","orcid":"https://orcid.org/0009-0009-3374-1941"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chris Ding","raw_affiliation_strings":["Chinese University of Hong Kong,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong,Shenzhen,China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.5719000101089478,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.5719000101089478,"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":0.5335000157356262,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.5045999884605408,"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":0.6433367133140564},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6357239484786987},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6280367374420166},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6026991009712219},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5934861898422241},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.494502991437912},{"id":"https://openalex.org/keywords/probabilistic-latent-semantic-analysis","display_name":"Probabilistic latent semantic analysis","score":0.4513120949268341},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32864895462989807},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24971354007720947}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6433367133140564},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6357239484786987},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6280367374420166},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6026991009712219},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5934861898422241},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.494502991437912},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.4513120949268341},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32864895462989807},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24971354007720947},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/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/icassp49660.2025.10890486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325571","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2048679005","https://openalex.org/W2101210369","https://openalex.org/W2107034620","https://openalex.org/W2119362355","https://openalex.org/W2533598788","https://openalex.org/W2555618208","https://openalex.org/W2725249286","https://openalex.org/W2898233200","https://openalex.org/W2903647084","https://openalex.org/W2998124973","https://openalex.org/W3024821730","https://openalex.org/W3098802639","https://openalex.org/W3148388528","https://openalex.org/W4224926219","https://openalex.org/W4237723258","https://openalex.org/W4295308223","https://openalex.org/W4321113904","https://openalex.org/W4386076075","https://openalex.org/W4392543743","https://openalex.org/W4392939918","https://openalex.org/W6637875599","https://openalex.org/W6638319203"],"related_works":["https://openalex.org/W4389358162","https://openalex.org/W2111020819","https://openalex.org/W2377594161","https://openalex.org/W1837533151","https://openalex.org/W2296297476","https://openalex.org/W2329943782","https://openalex.org/W1578340400","https://openalex.org/W2365514879","https://openalex.org/W84513934","https://openalex.org/W15987807"],"abstract_inverted_index":{"Effective":[0],"multi-view":[1,11,24,69],"subspace":[2,30,51,101],"learning":[3,74],"is":[4],"crucial":[5],"for":[6],"enhancing":[7],"classification":[8,25],"performance":[9],"on":[10,84,118],"data.":[12,70,112],"In":[13],"this":[14],"paper,":[15],"we":[16],"propose":[17],"CMvLSCN,":[18],"a":[19,48],"novel":[20],"end-to-end":[21],"framework":[22],"addressing":[23],"at":[26],"view,":[27],"sample,":[28],"and":[29,57,62,88,99,114],"levels.":[31],"The":[32],"key":[33],"innovations":[34],"are:":[35],"Strengthening":[36],"inter-view":[37,43],"consistency":[38],"within":[39],"categories":[40],"while":[41],"weakening":[42],"similarity":[44],"across":[45],"categories;":[46],"Learning":[47],"unified":[49],"latent":[50,60,86],"representation":[52,102],"through":[53],"the":[54,85],"view":[55],"fusion;":[56],"Imposing":[58],"low-rank":[59,82],"self-representation":[61],"hierarchical":[63],"contrastive":[64,73,91],"constraints":[65],"to":[66,75],"better":[67],"classify":[68],"CMvLSCN":[71],"employs":[72],"optimize":[76],"Kullback-Leibler":[77],"divergence":[78],"among":[79],"views,":[80],"imposes":[81],"structure":[83],"subspace,":[87],"introduces":[89],"sample-level":[90],"constraints.":[92],"This":[93],"approach":[94],"captures":[95],"underlying":[96],"data":[97],"relationships":[98],"enhances":[100],"discriminability.":[103],"Experiments":[104],"demonstrate":[105],"superior":[106],"performance,":[107],"especially":[108],"with":[109],"limited":[110],"training":[111],"Code":[113],"datasets":[115],"are":[116],"available":[117],"GitHub.":[119]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
