{"id":"https://openalex.org/W4206585896","doi":"https://doi.org/10.23919/eusipco54536.2021.9616303","title":"A Homotopy Optimization Method for Orthogonal Non-Negative Matrix Factorization","display_name":"A Homotopy Optimization Method for Orthogonal Non-Negative Matrix Factorization","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W4206585896","doi":"https://doi.org/10.23919/eusipco54536.2021.9616303"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco54536.2021.9616303","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco54536.2021.9616303","pdf_url":null,"source":{"id":"https://openalex.org/S4363607854","display_name":"2021 29th European Signal Processing Conference (EUSIPCO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th European Signal Processing Conference (EUSIPCO)","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/A5100459740","display_name":"Ya Liu","orcid":"https://orcid.org/0000-0002-4562-7654"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ya Liu","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR of China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR of China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025217534","display_name":"Mingjie Shao","orcid":"https://orcid.org/0000-0003-0659-5765"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjie Shao","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR of China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR of China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016986549","display_name":"Wing\u2010Kin Ma","orcid":"https://orcid.org/0000-0001-7314-3537"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wing-Kin Ma","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR of China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR of China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100459740"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.1307,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51267281,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1085","last_page":"1089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9937999844551086,"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/T10057","display_name":"Face and Expression Recognition","score":0.9937999844551086,"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":0.9847000241279602,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9749000072479248,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/orthogonality","display_name":"Orthogonality","score":0.6670487523078918},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6557115912437439},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5056440830230713},{"id":"https://openalex.org/keywords/homotopy","display_name":"Homotopy","score":0.5032879710197449},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.49715641140937805},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.46903643012046814},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.45850664377212524},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43008074164390564},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.3983641564846039},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3560802936553955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22296521067619324}],"concepts":[{"id":"https://openalex.org/C17137986","wikidata":"https://www.wikidata.org/wiki/Q215067","display_name":"Orthogonality","level":2,"score":0.6670487523078918},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6557115912437439},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5056440830230713},{"id":"https://openalex.org/C5961521","wikidata":"https://www.wikidata.org/wiki/Q746083","display_name":"Homotopy","level":2,"score":0.5032879710197449},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49715641140937805},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.46903643012046814},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.45850664377212524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43008074164390564},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.3983641564846039},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3560802936553955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22296521067619324},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco54536.2021.9616303","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco54536.2021.9616303","pdf_url":null,"source":{"id":"https://openalex.org/S4363607854","display_name":"2021 29th European Signal Processing Conference (EUSIPCO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5408317145","display_name":null,"funder_award_id":"CUHK 14208819","funder_id":"https://openalex.org/F4320335882","funder_display_name":"General Research Fund of Shanghai Normal University"}],"funders":[{"id":"https://openalex.org/F4320335882","display_name":"General Research Fund of Shanghai Normal University","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W331116093","https://openalex.org/W1902027874","https://openalex.org/W1970039276","https://openalex.org/W1992419399","https://openalex.org/W2015583498","https://openalex.org/W2043545458","https://openalex.org/W2061468236","https://openalex.org/W2086953401","https://openalex.org/W2101139104","https://openalex.org/W2113820768","https://openalex.org/W2145725490","https://openalex.org/W2150593711","https://openalex.org/W2153233077","https://openalex.org/W2189591224","https://openalex.org/W2606412288","https://openalex.org/W2939782843","https://openalex.org/W2969909702","https://openalex.org/W3018620303","https://openalex.org/W6611358592","https://openalex.org/W6674848643","https://openalex.org/W6687134308"],"related_works":["https://openalex.org/W2153775038","https://openalex.org/W2152353763","https://openalex.org/W2065762479","https://openalex.org/W2127243424","https://openalex.org/W2302542513","https://openalex.org/W2037504162","https://openalex.org/W4390394189","https://openalex.org/W2089917999","https://openalex.org/W2792706544","https://openalex.org/W1568451138"],"abstract_inverted_index":{"Data":[0],"clustering":[1,109,120],"is":[2],"a":[3,33,42,59,64,75,117],"key":[4],"problem":[5,56],"in":[6,67,111,116],"data":[7,24,113],"science":[8],"and":[9,55,115],"machine":[10],"learning.":[11],"In":[12],"this":[13],"paper,":[14],"we":[15,69],"consider":[16],"orthogonal":[17],"nonnegative":[18],"matrix":[19],"factorization":[20],"(ONMF)":[21],"for":[22],"scaled":[23],"clustering.":[25],"The":[26],"non-convex":[27],"orthogonality":[28],"constraint":[29],"of":[30,45,74,77],"ONMF":[31,46],"raises":[32],"great":[34],"challenge":[35],"from":[36,84],"an":[37],"optimization":[38],"viewpoint.":[39],"We":[40,61],"study":[41],"convex-constrained":[43],"transformation":[44],"that":[47,103],"allows":[48],"us":[49,95],"to":[50,87,96],"control":[51],"the":[52,71,78],"approximation":[53],"accuracy":[54],"difficulty":[57],"through":[58],"parameter.":[60],"then":[62],"apply":[63],"homotopy":[65,105],"strategy":[66],"which":[68],"trace":[70],"solution":[72],"path":[73],"sequence":[76],"aforementioned":[79],"transformed":[80],"problems,":[81],"gradually":[82],"moving":[83],"easy":[85],"problems":[86],"near-ONMF":[88],"problems.":[89],"Intuitively,":[90],"doing":[91],"so":[92],"may":[93],"allow":[94],"avoid":[97],"local":[98],"minima.":[99],"Numerical":[100],"results":[101],"show":[102],"our":[104],"method":[106],"yields":[107],"competitive":[108],"performance":[110],"synthetic":[112],"experiments":[114],"real-data":[118],"hyperspectral":[119],"experiment.":[121]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
