{"id":"https://openalex.org/W4416799123","doi":"https://doi.org/10.1109/apsipaasc65261.2025.11249282","title":"Nonnegative Matrix Factorization Using Dirichlet-Distribution-Based Regularization","display_name":"Nonnegative Matrix Factorization Using Dirichlet-Distribution-Based Regularization","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W4416799123","doi":"https://doi.org/10.1109/apsipaasc65261.2025.11249282"},"language":null,"primary_location":{"id":"doi:10.1109/apsipaasc65261.2025.11249282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc65261.2025.11249282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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":null,"display_name":"Haru Ogawa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160866","display_name":"National Institute of Technology, Kagawa College","ror":"https://ror.org/04xfwhf17","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210120810","https://openalex.org/I4210160866"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haru Ogawa","raw_affiliation_strings":["National Institute of Technology, Kagawa College,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology, Kagawa College,Japan","institution_ids":["https://openalex.org/I4210160866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071479017","display_name":"Daichi Kitamura","orcid":"https://orcid.org/0000-0003-1117-7939"},"institutions":[{"id":"https://openalex.org/I4210160866","display_name":"National Institute of Technology, Kagawa College","ror":"https://ror.org/04xfwhf17","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210120810","https://openalex.org/I4210160866"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daichi Kitamura","raw_affiliation_strings":["National Institute of Technology, Kagawa College,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology, Kagawa College,Japan","institution_ids":["https://openalex.org/I4210160866"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104579621","display_name":"Shoma Ayano","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160866","display_name":"National Institute of Technology, Kagawa College","ror":"https://ror.org/04xfwhf17","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210120810","https://openalex.org/I4210160866"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shoma Ayano","raw_affiliation_strings":["National Institute of Technology, Kagawa College,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology, Kagawa College,Japan","institution_ids":["https://openalex.org/I4210160866"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210160866"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32249002,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1229","last_page":"1234"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.4163999855518341,"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":0.4163999855518341,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.16850000619888306,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.07479999959468842,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8895999789237976},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.736299991607666},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.5568000078201294},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.501800000667572},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4932999908924103},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.46540001034736633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4607999920845032},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4505000114440918}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8895999789237976},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.736299991607666},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5662999749183655},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.5568000078201294},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5220999717712402},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.501800000667572},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4932999908924103},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.46540001034736633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4607999920845032},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4505000114440918},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.42309999465942383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4000999927520752},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38510000705718994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3840999901294708},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3346000015735626},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.3249000012874603},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C139018669","wikidata":"https://www.wikidata.org/wiki/Q6961560","display_name":"Nonnegative matrix","level":4,"score":0.27549999952316284},{"id":"https://openalex.org/C2778258933","wikidata":"https://www.wikidata.org/wiki/Q16918986","display_name":"Decomposition method (queueing theory)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc65261.2025.11249282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc65261.2025.11249282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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":16,"referenced_works":["https://openalex.org/W2082740732","https://openalex.org/W2091665187","https://openalex.org/W2127851351","https://openalex.org/W2146913572","https://openalex.org/W2150415460","https://openalex.org/W2412956798","https://openalex.org/W2508393166","https://openalex.org/W2605327034","https://openalex.org/W2783473931","https://openalex.org/W2947659587","https://openalex.org/W2954682230","https://openalex.org/W2987283719","https://openalex.org/W3095117838","https://openalex.org/W4200201178","https://openalex.org/W4206329804","https://openalex.org/W4285483548"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,17,21,32,78,94,99],"novel":[6],"nonnegative":[7,22],"matrix":[8,23],"factorization":[9],"(NMF)":[10],"using":[11],"Dirichlet":[12],"distribution":[13],"prior.":[14],"NMF":[15,40,61,104],"is":[16,25,88],"low-rank":[18],"approximation":[19],"of":[20,38,57,84,108],"and":[24,44,46,98,125],"widely":[26],"used":[27],"in":[28,31,54,77,105,121],"various":[29],"tasks":[30],"signal":[33,127],"processing":[34,128],"field.":[35],"Many":[36],"variants":[37],"regularized":[39],"have":[41],"been":[42],"proposed,":[43],"sparse":[45],"smooth":[47],"regularizations":[48],"particularly":[49],"play":[50],"an":[51],"important":[52],"role":[53],"the":[55,85,106,115],"history":[56],"NMF.":[58],"The":[59,82,111],"proposed":[60,86,116],"utilizes":[62],"Dirichlet-distribution-based":[63],"regularization,":[64],"which":[65],"enables":[66],"us":[67],"to":[68,74],"impose":[69],"either":[70],"sparseness":[71],"or":[72],"smoothness":[73],"decomposed":[75],"matrices":[76],"single":[79],"unified":[80],"framework.":[81],"effectiveness":[83],"method":[87],"demonstrated":[89],"through":[90],"numerical":[91],"experiments,":[92],"including":[93],"decomposition":[95,123],"accuracy":[96],"evaluation":[97],"comparison":[100],"with":[101],"conventional":[102],"sparsity-regularized":[103],"task":[107],"howling":[109],"suppression.":[110],"results":[112],"confirm":[113],"that":[114],"approach":[117],"achieves":[118],"improved":[119],"performance":[120],"both":[122],"quality":[124],"practical":[126],"applications.":[129]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-28T00:00:00"}