{"id":"https://openalex.org/W4406458116","doi":"https://doi.org/10.1109/bigdata62323.2024.10825312","title":"Stochastic Scale Invariant Power Iteration for KL-divergence Nonnegative Matrix Factorization","display_name":"Stochastic Scale Invariant Power Iteration for KL-divergence Nonnegative Matrix Factorization","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458116","doi":"https://doi.org/10.1109/bigdata62323.2024.10825312"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5101512307","display_name":"Cheol\u2010Min Kim","orcid":"https://orcid.org/0000-0002-7242-1061"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cheolmin Kim","raw_affiliation_strings":["Northwestern University,Department of Industrial Engineering and Management Sciences,Evanston,USA"],"affiliations":[{"raw_affiliation_string":"Northwestern University,Department of Industrial Engineering and Management Sciences,Evanston,USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100600319","display_name":"Young\u2010Seok Kim","orcid":"https://orcid.org/0000-0002-8486-9162"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Youngseok Kim","raw_affiliation_strings":["University of Chicago,Department of Statistics,Chicago,USA"],"affiliations":[{"raw_affiliation_string":"University of Chicago,Department of Statistics,Chicago,USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087924643","display_name":"Yegna Subramanian Jambunath","orcid":null},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yegna Subramanian Jambunath","raw_affiliation_strings":["Northwestern University,Center for Deep Learning,Evanston,USA"],"affiliations":[{"raw_affiliation_string":"Northwestern University,Center for Deep Learning,Evanston,USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013049879","display_name":"Diego Klabjan","orcid":"https://orcid.org/0000-0003-4213-9281"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Diego Klabjan","raw_affiliation_strings":["Northwestern University,Department of Industrial Engineering and Management Sciences,Evanston,USA"],"affiliations":[{"raw_affiliation_string":"Northwestern University,Department of Industrial Engineering and Management Sciences,Evanston,USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101512307"],"corresponding_institution_ids":["https://openalex.org/I111979921"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26637353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"969","last_page":"977"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9983999729156494,"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":0.9983999729156494,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9977999925613403,"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/invariant","display_name":"Invariant (physics)","score":0.6273126602172852},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5574227571487427},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5402642488479614},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5270167589187622},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5175763368606567},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5050762295722961},{"id":"https://openalex.org/keywords/scale-invariance","display_name":"Scale invariance","score":0.5009870529174805},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4395492970943451},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.431448757648468},{"id":"https://openalex.org/keywords/matrix-algebra","display_name":"Matrix algebra","score":0.41466644406318665},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3395882546901703},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.211062490940094},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1434658169746399},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09504932165145874}],"concepts":[{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6273126602172852},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5574227571487427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5402642488479614},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5270167589187622},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5175763368606567},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5050762295722961},{"id":"https://openalex.org/C135593079","wikidata":"https://www.wikidata.org/wiki/Q1750766","display_name":"Scale invariance","level":2,"score":0.5009870529174805},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4395492970943451},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.431448757648468},{"id":"https://openalex.org/C2988995629","wikidata":"https://www.wikidata.org/wiki/Q2915729","display_name":"Matrix algebra","level":3,"score":0.41466644406318665},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3395882546901703},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.211062490940094},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1434658169746399},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09504932165145874},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1548802052","https://openalex.org/W2022712430","https://openalex.org/W2050583479","https://openalex.org/W2110096996","https://openalex.org/W2114508388","https://openalex.org/W2135029798","https://openalex.org/W2139813506","https://openalex.org/W2144359569","https://openalex.org/W2166021275","https://openalex.org/W2333315597","https://openalex.org/W2432567885","https://openalex.org/W2538881007","https://openalex.org/W2553108847","https://openalex.org/W2555690212","https://openalex.org/W2556206132","https://openalex.org/W2806897640","https://openalex.org/W2921315455","https://openalex.org/W2945743233","https://openalex.org/W2963716678","https://openalex.org/W2978664318","https://openalex.org/W3106246664","https://openalex.org/W3190812686","https://openalex.org/W4235926321","https://openalex.org/W4250857377","https://openalex.org/W4294166991","https://openalex.org/W4399359197","https://openalex.org/W6639271350","https://openalex.org/W6639299341","https://openalex.org/W6680012447","https://openalex.org/W6684710191","https://openalex.org/W6684753248","https://openalex.org/W6685973902","https://openalex.org/W6702811211","https://openalex.org/W6729268309","https://openalex.org/W6730186959","https://openalex.org/W6741930749","https://openalex.org/W6762969942","https://openalex.org/W6780029851","https://openalex.org/W6784041521"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W2069570686"],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,36,69],"mini-batch":[3],"stochastic":[4,37,106],"variance-reduced":[5],"algorithm":[6,34],"to":[7,45],"solve":[8],"finite-sum":[9],"scale":[10,40],"invariant":[11,41],"problems":[12],"which":[13],"cover":[14],"several":[15],"examples":[16],"in":[17],"machine":[18],"learning":[19],"and":[20,28,83,99],"statistics":[21],"such":[22],"as":[23],"principal":[24],"component":[25],"analysis":[26],"(PCA)":[27],"estimation":[29],"of":[30,39,63],"mixture":[31],"proportions.":[32],"The":[33],"is":[35,50],"generalization":[38],"power":[42,46],"iteration,":[43],"specializing":[44],"iteration":[47],"when":[48],"full-batch":[49],"used":[51],"for":[52],"the":[53,61,64,76,89,94,104],"PCA":[54],"problem.":[55],"In":[56],"convergence":[57],"analysis,":[58],"we":[59],"show":[60],"expectation":[62],"optimality":[65],"gap":[66],"decreases":[67],"at":[68],"linear":[70],"rate":[71],"under":[72],"some":[73],"conditions":[74],"on":[75,88],"step":[77],"size,":[78],"epoch":[79],"length,":[80],"batch":[81],"size":[82],"initial":[84],"iterate.":[85],"Numerical":[86],"experiments":[87],"non-negative":[90],"factorization":[91],"problem":[92],"with":[93],"KullbackLeibler":[95],"divergence":[96],"using":[97],"real":[98],"synthetic":[100],"datasets":[101],"demonstrate":[102],"that":[103],"proposed":[105],"approach":[107],"not":[108],"only":[109],"converges":[110],"faster":[111],"than":[112],"state-of-the-art":[113],"deterministic":[114],"algorithms":[115],"but":[116],"also":[117],"produces":[118],"excellent":[119],"quality":[120],"robust":[121],"solutions.":[122]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
