{"id":"https://openalex.org/W3095838991","doi":"https://doi.org/10.1109/ita50056.2020.9245004","title":"Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data","display_name":"Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data","publication_year":2020,"publication_date":"2020-02-02","ids":{"openalex":"https://openalex.org/W3095838991","doi":"https://doi.org/10.1109/ita50056.2020.9245004","mag":"3095838991"},"language":"en","primary_location":{"id":"doi:10.1109/ita50056.2020.9245004","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ita50056.2020.9245004","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Information Theory and Applications Workshop (ITA)","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/A5065059104","display_name":"Hanbaek Lyu","orcid":"https://orcid.org/0000-0002-6323-5240"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanbaek Lyu","raw_affiliation_strings":["University of California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, CA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033422362","display_name":"Georg Menz","orcid":"https://orcid.org/0000-0001-9295-5063"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Georg Menz","raw_affiliation_strings":["University of California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, CA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024153474","display_name":"Deanna Needell","orcid":"https://orcid.org/0000-0002-8058-8638"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deanna Needell","raw_affiliation_strings":["University of California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, CA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039804631","display_name":"Christopher Strohmeier","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Strohmeier","raw_affiliation_strings":["University of California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, CA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1958,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51211319,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"11","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9911999702453613,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9911999702453613,"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":0.9835000038146973,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9769999980926514,"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":0.7697198390960693},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7368921637535095},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.727762758731842},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.5196741223335266},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5069425106048584},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5030738711357117},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4841390550136566},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43100103735923767},{"id":"https://openalex.org/keywords/nonnegative-matrix","display_name":"Nonnegative matrix","score":0.41242292523384094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4040379822254181},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40213850140571594},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33319616317749023},{"id":"https://openalex.org/keywords/symmetric-matrix","display_name":"Symmetric matrix","score":0.18510392308235168}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.7697198390960693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7368921637535095},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.727762758731842},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5196741223335266},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5069425106048584},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5030738711357117},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4841390550136566},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43100103735923767},{"id":"https://openalex.org/C139018669","wikidata":"https://www.wikidata.org/wiki/Q6961560","display_name":"Nonnegative matrix","level":4,"score":0.41242292523384094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4040379822254181},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40213850140571594},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33319616317749023},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.18510392308235168},{"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ita50056.2020.9245004","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ita50056.2020.9245004","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Information Theory and Applications Workshop (ITA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6499999761581421,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1591116419","https://openalex.org/W1854811422","https://openalex.org/W1902027874","https://openalex.org/W1987972509","https://openalex.org/W2017288758","https://openalex.org/W2038136467","https://openalex.org/W2076554482","https://openalex.org/W2079196839","https://openalex.org/W2103146144","https://openalex.org/W2112447569","https://openalex.org/W2118718620","https://openalex.org/W2135029798","https://openalex.org/W2589014227","https://openalex.org/W2750342461","https://openalex.org/W2781090973","https://openalex.org/W2987964156","https://openalex.org/W3101790962","https://openalex.org/W4235713725","https://openalex.org/W4288028785","https://openalex.org/W6639041367","https://openalex.org/W6676727762","https://openalex.org/W6677759377","https://openalex.org/W6680012447","https://openalex.org/W6770252875"],"related_works":["https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2108919995","https://openalex.org/W2022978200","https://openalex.org/W3099441337","https://openalex.org/W2731733684","https://openalex.org/W2083358384","https://openalex.org/W2768089427","https://openalex.org/W1989034480"],"abstract_inverted_index":{"Online":[0],"nonnegative":[1,55],"matrix":[2,7,24,56],"factorization":[3,8,57],"(ONMF)":[4],"is":[5],"a":[6,19,73],"technique":[9,91],"in":[10,18,92],"the":[11,23,39,93],"online":[12,54],"setting":[13],"where":[14],"data":[15,43,69,80],"are":[16,26],"acquired":[17],"streaming":[20],"fashion":[21],"and":[22,102],"factors":[25],"updated":[27],"each":[28],"time.":[29],"This":[30],"enables":[31],"factor":[32],"analysis":[33],"to":[34,59],"be":[35],"performed":[36],"concurrently":[37],"with":[38],"arrival":[40],"of":[41,67,96],"new":[42],"samples.":[44],"In":[45],"this":[46],"article,":[47],"we":[48],"demonstrate":[49,87],"how":[50],"one":[51],"can":[52],"use":[53],"algorithms":[58],"learn":[60],"joint":[61],"dictionary":[62,75,89],"atoms":[63],"from":[64],"an":[65],"ensemble":[66],"correlated":[68],"sets.":[70],"We":[71,86],"propose":[72],"temporal":[74],"learning":[76,90],"scheme":[77],"for":[78],"time-series":[79],"sets,":[81],"based":[82],"on":[83],"ONMF":[84],"algorithms.":[85],"our":[88],"application":[94],"contexts":[95],"historical":[97],"temperature":[98],"data,":[99],"video":[100],"frames,":[101],"color":[103],"images.":[104]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
