{"id":"https://openalex.org/W2938315196","doi":"https://doi.org/10.1109/icassp.2019.8682508","title":"Stochastic Ml Simplex-structured Matrix Factorization under the Dirichlet Mixture Model","display_name":"Stochastic Ml Simplex-structured Matrix Factorization under the Dirichlet Mixture Model","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2938315196","doi":"https://doi.org/10.1109/icassp.2019.8682508","mag":"2938315196"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5057100970","display_name":"Ruiyuan Wu","orcid":"https://orcid.org/0000-0002-7751-4355"},"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":"Ruiyuan Wu","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429879","display_name":"Qiang Li","orcid":"https://orcid.org/0000-0001-5609-3320"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Li","raw_affiliation_strings":["School of Info. & Comm. Eng., University of Electronic Science and Technology of China, China"],"affiliations":[{"raw_affiliation_string":"School of Info. & Comm. Eng., University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"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, Shatin, N.T., Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057100970"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.5356,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.6992555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"16","issue":null,"first_page":"5561","last_page":"5565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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/T10057","display_name":"Face and Expression Recognition","score":0.9919999837875366,"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":0.9853000044822693,"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/simplex","display_name":"Simplex","score":0.5907782912254333},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5807059407234192},{"id":"https://openalex.org/keywords/coefficient-matrix","display_name":"Coefficient matrix","score":0.5379320979118347},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.48544079065322876},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47139695286750793},{"id":"https://openalex.org/keywords/simplex-algorithm","display_name":"Simplex algorithm","score":0.4709376394748688},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.43546515703201294},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.4338959753513336},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.43020346760749817},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4286385774612427},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4285547435283661},{"id":"https://openalex.org/keywords/maximum-likelihood-sequence-estimation","display_name":"Maximum likelihood sequence estimation","score":0.42489081621170044},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3817976713180542},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.34768009185791016},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.19525757431983948},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.1373438835144043},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.09660425782203674},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09607183933258057}],"concepts":[{"id":"https://openalex.org/C62438384","wikidata":"https://www.wikidata.org/wiki/Q331350","display_name":"Simplex","level":2,"score":0.5907782912254333},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5807059407234192},{"id":"https://openalex.org/C60866291","wikidata":"https://www.wikidata.org/wiki/Q5140577","display_name":"Coefficient matrix","level":3,"score":0.5379320979118347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.48544079065322876},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47139695286750793},{"id":"https://openalex.org/C144521790","wikidata":"https://www.wikidata.org/wiki/Q134164","display_name":"Simplex algorithm","level":3,"score":0.4709376394748688},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.43546515703201294},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.4338959753513336},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.43020346760749817},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4286385774612427},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4285547435283661},{"id":"https://openalex.org/C191462741","wikidata":"https://www.wikidata.org/wiki/Q6795902","display_name":"Maximum likelihood sequence estimation","level":3,"score":0.42489081621170044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3817976713180542},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.34768009185791016},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.19525757431983948},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.1373438835144043},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.09660425782203674},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09607183933258057},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2019.8682508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682508","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W190008395","https://openalex.org/W1246381107","https://openalex.org/W1513873506","https://openalex.org/W1608180792","https://openalex.org/W1854811422","https://openalex.org/W1902027874","https://openalex.org/W1966872876","https://openalex.org/W1976615758","https://openalex.org/W2018158121","https://openalex.org/W2050968963","https://openalex.org/W2063790512","https://openalex.org/W2081555128","https://openalex.org/W2101837437","https://openalex.org/W2111604514","https://openalex.org/W2129062845","https://openalex.org/W2136635436","https://openalex.org/W2149414429","https://openalex.org/W2163886442","https://openalex.org/W2169924573","https://openalex.org/W2185164352","https://openalex.org/W2294586855","https://openalex.org/W2513096609","https://openalex.org/W2698933417","https://openalex.org/W3100202987","https://openalex.org/W6607826182","https://openalex.org/W6639041367","https://openalex.org/W6785687179"],"related_works":["https://openalex.org/W2166485459","https://openalex.org/W2185826091","https://openalex.org/W2048470382","https://openalex.org/W2477407501","https://openalex.org/W2384679317","https://openalex.org/W2911215968","https://openalex.org/W1570109187","https://openalex.org/W1583787753","https://openalex.org/W2491692165","https://openalex.org/W2366013513"],"abstract_inverted_index":{"Simplex-structured":[0],"matrix":[1,11,111],"factorization":[2],"(SSMF)":[3],"is":[4,90,127,153],"a":[5,9,54,70,85,94,123],"problem":[6,133],"of":[7],"recovering":[8],"basis":[10,110],"and":[12,46,103,112,126,129,148],"the":[13,20,28,63,100,109,132,157,168],"corresponding":[14],"coefficient":[15,21,64,101],"vectors":[16,22,65],"from":[17],"data,":[18,84],"where":[19],"are":[23],"constrained":[24],"to":[25,76,99,107,135],"lie":[26],"in":[27,36,82,174],"unit":[29],"simplex.":[30],"SSMF":[31,89],"has":[32],"attracted":[33],"growing":[34],"attention":[35],"recent":[37],"years,":[38],"with":[39,97],"numerous":[40],"applications":[41,161],"such":[42],"as":[43,66],"hyperspectral":[44],"unmixing":[45],"document":[47],"clustering.":[48],"In":[49],"this":[50,130,139],"work,":[51],"we":[52],"develop":[53],"maximum-likelihood":[55],"(ML)":[56],"approach":[57],"for":[58,88],"SSMF.":[59],"Specifically,":[60],"by":[61,162],"modeling":[62],"random":[67],"variables":[68],"following":[69],"Dirichlet":[71,114],"mixture":[72,115],"distribution-which":[73],"allows":[74],"us":[75],"model":[77,87],"more":[78],"complex":[79],"data":[80],"distributions":[81],"real-life":[83],"probabilistic":[86],"employed.":[91],"We":[92,155],"consider":[93,156],"marginalized":[95,118],"likelihood":[96,119],"respect":[98],"vectors,":[102],"use":[104],"ML":[105],"estimation":[106],"learn":[108],"unknown":[113],"parameters.":[116],"The":[117],"does":[120],"not":[121],"admit":[122],"closed":[124],"form":[125],"non-concave,":[128],"makes":[131],"challenging":[134],"solve.":[136],"To":[137],"handle":[138],"challenge,":[140],"an":[141],"effective":[142],"algorithm":[143,170],"using":[144],"sample":[145],"average":[146],"approximation":[147],"block":[149],"successive":[150],"upper-bound":[151],"minimization":[152],"proposed.":[154],"aforementioned":[158],"two":[159],"real-world":[160],"simulations.":[163],"Numerical":[164],"results":[165],"show":[166],"that":[167],"proposed":[169],"delivers":[171],"appealing":[172],"performance":[173],"both":[175],"applications.":[176]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
