{"id":"https://openalex.org/W2898975278","doi":"https://doi.org/10.1109/mlsp.2018.8516924","title":"VARIATIONAL BAYESIAN PARTIALLY OBSERVED NON-NEGATIVE TENSOR FACTORIZATION","display_name":"VARIATIONAL BAYESIAN PARTIALLY OBSERVED NON-NEGATIVE TENSOR FACTORIZATION","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2898975278","doi":"https://doi.org/10.1109/mlsp.2018.8516924","mag":"2898975278"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2018.8516924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2018.8516924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5015817855","display_name":"Jesper L\u00f8ve Hinrich","orcid":"https://orcid.org/0000-0003-0258-7151"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Jesper L. Hinrich","raw_affiliation_strings":["DTU Compute, Technical University of Denmark, Denmark"],"affiliations":[{"raw_affiliation_string":"DTU Compute, Technical University of Denmark, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023706408","display_name":"S\u00f8ren F. V. Nielsen","orcid":"https://orcid.org/0000-0001-6713-9144"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Soren F. V. Nielsen","raw_affiliation_strings":["DTU Compute, Technical University of Denmark, Denmark"],"affiliations":[{"raw_affiliation_string":"DTU Compute, Technical University of Denmark, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032991538","display_name":"Kristoffer H. Madsen","orcid":"https://orcid.org/0000-0001-8606-7641"},"institutions":[{"id":"https://openalex.org/I2801942218","display_name":"Hvidovre Hospital","ror":"https://ror.org/00edrn755","country_code":"DK","type":"healthcare","lineage":["https://openalex.org/I2801942218","https://openalex.org/I2802567020"]},{"id":"https://openalex.org/I2802567020","display_name":"Copenhagen University Hospital","ror":"https://ror.org/05bpbnx46","country_code":"DK","type":"healthcare","lineage":["https://openalex.org/I2802567020"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Kristoffer H. Madsen","raw_affiliation_strings":["Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital, Hvidovre, Denmark"],"affiliations":[{"raw_affiliation_string":"Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital, Hvidovre, Denmark","institution_ids":["https://openalex.org/I2801942218","https://openalex.org/I2802567020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059840085","display_name":"Morten M\u00f8rup","orcid":"https://orcid.org/0000-0003-4985-4368"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Morten Morup","raw_affiliation_strings":["DTU Compute, Technical University of Denmark, Denmark"],"affiliations":[{"raw_affiliation_string":"DTU Compute, Technical University of Denmark, Denmark","institution_ids":["https://openalex.org/I96673099"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015817855"],"corresponding_institution_ids":["https://openalex.org/I96673099"],"apc_list":null,"apc_paid":null,"fwci":0.5031,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.58390177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10269","display_name":"Epigenetics and DNA Methylation","score":0.930400013923645,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.9125999808311462,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.9229756593704224},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6221040487289429},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.613728404045105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6066796183586121},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6052486896514893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5754358768463135},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5334468483924866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5279416441917419},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4557182490825653},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3085227906703949},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28190362453460693},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08717837929725647}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.9229756593704224},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6221040487289429},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.613728404045105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6066796183586121},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6052486896514893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5754358768463135},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5334468483924866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5279416441917419},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4557182490825653},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3085227906703949},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28190362453460693},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08717837929725647},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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":2,"locations":[{"id":"doi:10.1109/mlsp.2018.8516924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2018.8516924","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/abd58193-b105-4e85-86d9-b6be4a741f25","is_oa":false,"landing_page_url":"https://orbit.dtu.dk/en/publications/abd58193-b105-4e85-86d9-b6be4a741f25","pdf_url":null,"source":{"id":"https://openalex.org/S4306400705","display_name":"Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I96673099","host_organization_name":"Technical University of Denmark","host_organization_lineage":["https://openalex.org/I96673099"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Hinrich , J L , Nielsen , S F V , Madsen , K H &amp; M\u00f8rup , M 2018 , Variational bayesian partially observed non-negative tensor factorization . in Proceedings of 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing . IEEE , pp. 1-6 , 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing , Aalborg , Denmark , 17/09/2018 . https://doi.org/10.1109/MLSP.2018.8516924","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1246381107","https://openalex.org/W1594523130","https://openalex.org/W1902027874","https://openalex.org/W2024165284","https://openalex.org/W2049526013","https://openalex.org/W2055655674","https://openalex.org/W2059745395","https://openalex.org/W2079231426","https://openalex.org/W2091571775","https://openalex.org/W2130170723","https://openalex.org/W2136468592","https://openalex.org/W2738412876","https://openalex.org/W2806958733","https://openalex.org/W3103867094"],"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/W34555840"],"abstract_inverted_index":{"Non-negative":[0],"matrix":[1],"and":[2,32,66,74,83,94,100,117],"tensor":[3,56],"factorization":[4,57],"(NMF/NTF)":[5],"have":[6],"become":[7],"important":[8],"tools":[9],"for":[10,30,59,112],"extracting":[11],"part":[12],"based":[13],"representations":[14],"in":[15,90],"data.":[16,43,62],"It":[17],"is":[18,27,133,140],"however":[19],"unclear":[20],"when":[21,38,135],"an":[22],"NMF":[23,52],"or":[24],"NTF":[25],"approach":[26],"most":[28],"suited":[29],"data":[31,125,139],"how":[33],"reliably":[34],"the":[35,78,91,96,106,143],"models":[36],"predict":[37],"trained":[39],"on":[40,81],"partially":[41,60,123],"observed":[42,61,124],"We":[44,76,103],"presently":[45],"extend":[46],"a":[47,84],"recently":[48],"proposed":[49],"variational":[50],"Bayesian":[51],"(VB-NMF)":[53],"to":[54,98],"non-negative":[55],"(VB-NTF)":[58],"This":[63],"admits":[64],"bi-":[65],"multi-linear":[67],"structure":[68],"quantification":[69],"considering":[70],"both":[71],"model":[72,144],"prediction":[73],"evidence.":[75],"evaluate":[77],"developed":[79],"VB-NTF":[80,116],"synthetic":[82],"real":[85],"dataset":[86],"of":[87,138],"gene":[88,107],"expression":[89],"human":[92],"brain":[93],"contrast":[95],"performance":[97],"VB-NMF":[99,114],"conventional":[101,127],"NMF/NTF.":[102,128],"find":[104],"that":[105,118],"expressions":[108],"are":[109],"better":[110],"accounted":[111],"by":[113],"than":[115,126],"VB-NMF/VB-NTF":[119],"more":[120],"robustly":[121],"handle":[122],"In":[129],"particular,":[130],"probabilistic":[131],"modeling":[132],"beneficial":[134],"large":[136],"amounts":[137],"missing":[141],"and/or":[142],"order":[145],"over-specified.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
