{"id":"https://openalex.org/W2019454299","doi":"https://doi.org/10.1109/tmm.2014.2307692","title":"Variational Bayesian Methods For Multimedia Problems","display_name":"Variational Bayesian Methods For Multimedia Problems","publication_year":2014,"publication_date":"2014-02-24","ids":{"openalex":"https://openalex.org/W2019454299","doi":"https://doi.org/10.1109/tmm.2014.2307692","mag":"2019454299"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2014.2307692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2014.2307692","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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/A5038051409","display_name":"Zhaofu Chen","orcid":"https://orcid.org/0000-0001-6827-839X"},"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":"Zhaofu Chen","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA","Department of Electrical Engineering and Computer Science, Northwestern University , Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Northwestern University , Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107868098","display_name":"S. Derin Babacan","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Derin Babacan","raw_affiliation_strings":["Google Inc., Mountain View, CA, USA","Google Inc., Mountain View, CA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc., Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Inc., Mountain View, CA USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023830568","display_name":"Rafael Molina","orcid":"https://orcid.org/0000-0003-4694-8588"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Rafael Molina","raw_affiliation_strings":["el Departmento de Ciencias de la Computacion e I.A. E.T.S. Ing. Informatica y Teleomunicacion, Universidad de Granada, Granada, Spain","el Departmento de Ciencias de la Computacion e I.A. E.T.S. Ing. Informatica y Teleomunicacion, Universidad de Granada, Granada, Spain#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"el Departmento de Ciencias de la Computacion e I.A. E.T.S. Ing. Informatica y Teleomunicacion, Universidad de Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]},{"raw_affiliation_string":"el Departmento de Ciencias de la Computacion e I.A. E.T.S. Ing. Informatica y Teleomunicacion, Universidad de Granada, Granada, Spain#TAB#","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048650003","display_name":"Aggelos K. Katsaggelos","orcid":"https://orcid.org/0000-0003-4554-0070"},"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":"Aggelos K. Katsaggelos","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA","Department of Electrical Engineering and Computer Science, Northwestern University , Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Northwestern University , Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.2127,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.96358433,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"16","issue":"4","first_page":"1000","last_page":"1017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9889000058174133,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7780935764312744},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.765799343585968},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.71415114402771},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6447776556015015},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.6188868284225464},{"id":"https://openalex.org/keywords/expectation-propagation","display_name":"Expectation propagation","score":0.5588546395301819},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5503479838371277},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.5277861952781677},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.49544060230255127},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.48205575346946716},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4788648784160614},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.46971622109413147},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.46712830662727356},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.43813174962997437},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4379444122314453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42809611558914185},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4245951175689697},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4063635766506195},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38092041015625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1410902440547943},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.08870053291320801}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7780935764312744},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.765799343585968},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.71415114402771},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6447776556015015},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.6188868284225464},{"id":"https://openalex.org/C2779363554","wikidata":"https://www.wikidata.org/wiki/Q5420835","display_name":"Expectation propagation","level":4,"score":0.5588546395301819},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5503479838371277},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.5277861952781677},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.49544060230255127},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.48205575346946716},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4788648784160614},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.46971622109413147},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.46712830662727356},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.43813174962997437},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4379444122314453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42809611558914185},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4245951175689697},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4063635766506195},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38092041015625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1410902440547943},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.08870053291320801},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tmm.2014.2307692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2014.2307692","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.650.617","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.650.617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ivpl.ece.northwestern.edu/system/files/zhaofu_MM.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.650.7710","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.650.7710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://decsai.ugr.es/vip/files/journals/TMMVB.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W1496451467","https://openalex.org/W1503398984","https://openalex.org/W1511986666","https://openalex.org/W1515272691","https://openalex.org/W1579935095","https://openalex.org/W1590183771","https://openalex.org/W1648445109","https://openalex.org/W1723619723","https://openalex.org/W1795014501","https://openalex.org/W1880262756","https://openalex.org/W1934021597","https://openalex.org/W1970948570","https://openalex.org/W1971269812","https://openalex.org/W1978380426","https://openalex.org/W1991255919","https://openalex.org/W2000721204","https://openalex.org/W2007087405","https://openalex.org/W2013442351","https://openalex.org/W2020999234","https://openalex.org/W2021093529","https://openalex.org/W2027802637","https://openalex.org/W2049633694","https://openalex.org/W2059283452","https://openalex.org/W2063392856","https://openalex.org/W2071415508","https://openalex.org/W2071494625","https://openalex.org/W2073414385","https://openalex.org/W2082206048","https://openalex.org/W2083176148","https://openalex.org/W2089679078","https://openalex.org/W2093922090","https://openalex.org/W2098062695","https://openalex.org/W2109240917","https://openalex.org/W2109389234","https://openalex.org/W2110764733","https://openalex.org/W2114113040","https://openalex.org/W2115979064","https://openalex.org/W2119367754","https://openalex.org/W2119507238","https://openalex.org/W2119556711","https://openalex.org/W2121274305","https://openalex.org/W2121486117","https://openalex.org/W2122646361","https://openalex.org/W2125392257","https://openalex.org/W2126819395","https://openalex.org/W2134601045","https://openalex.org/W2136634080","https://openalex.org/W2136870201","https://openalex.org/W2149021215","https://openalex.org/W2149606063","https://openalex.org/W2158694395","https://openalex.org/W2159080219","https://openalex.org/W2159382562","https://openalex.org/W2161050705","https://openalex.org/W2163940565","https://openalex.org/W2164098335","https://openalex.org/W2165363188","https://openalex.org/W2167270514","https://openalex.org/W2296319761","https://openalex.org/W2540621430","https://openalex.org/W2547826090","https://openalex.org/W2548692314","https://openalex.org/W2963762195","https://openalex.org/W2990138404","https://openalex.org/W2991334544","https://openalex.org/W3145164839","https://openalex.org/W4211049957","https://openalex.org/W4237791300","https://openalex.org/W4237840503","https://openalex.org/W4246070010","https://openalex.org/W4249667877","https://openalex.org/W4250589301","https://openalex.org/W4285719527","https://openalex.org/W6638563174","https://openalex.org/W6640231202","https://openalex.org/W6834357723"],"related_works":["https://openalex.org/W2097107341","https://openalex.org/W2612895134","https://openalex.org/W4297779426","https://openalex.org/W2952920919","https://openalex.org/W3003852655","https://openalex.org/W2129270363","https://openalex.org/W2298902871","https://openalex.org/W2963050343","https://openalex.org/W1520194733","https://openalex.org/W2019454299"],"abstract_inverted_index":{"In":[0,89],"this":[1,90,172],"paper":[2,91],"we":[3,92],"present":[4,151],"an":[5],"introduction":[6],"to":[7,58,69],"Variational":[8],"Bayesian":[9,182],"(VB)":[10],"methods":[11,103,125,183],"in":[12,23,61,191],"the":[13,85,95,106,113,131,157,162,174],"context":[14],"of":[15,31,161,181],"probabilistic":[16],"graphical":[17,139],"models,":[18,140],"and":[19,48,84,99,112,121,159,184],"discuss":[20],"their":[21],"application":[22],"multimedia":[24,153],"related":[25,154],"problems.":[26],"VB":[27,54,98,120,147,163],"is":[28,56,66],"a":[29,146,178],"family":[30],"deterministic":[32],"probability":[33],"distribution":[34],"approximation":[35,102],"procedures":[36],"that":[37,126,169],"offer":[38],"distinct":[39],"advantages":[40],"over":[41],"alternative":[42,76],"approaches":[43,78],"based":[44,129],"on":[45,130],"stochastic":[46],"sampling":[47],"those":[49],"providing":[50],"only":[51],"point":[52],"estimates.":[53],"inference":[55,77,148],"flexible":[57],"be":[59,143],"applied":[60],"different":[62],"practical":[63],"problems,":[64],"yet":[65],"broad":[67],"enough":[68],"subsume":[70],"as":[71,105,145],"its":[72],"special":[73],"cases":[74],"several":[75,152],"including":[79],"Maximum":[80],"A":[81],"Posteriori":[82],"(MAP)":[83],"Expectation-Maximization":[86],"(EM)":[87],"algorithm.":[88],"also":[93,142],"show":[94],"connections":[96,186],"between":[97],"other":[100],"posterior":[101],"such":[104],"marginalization-based":[107],"Loopy":[108],"Belief":[109],"Propagation":[110,115],"(LBP)":[111],"Expectation":[114],"(EP)":[116],"algorithms.":[117],"Specifically,":[118],"both":[119],"EP":[122],"are":[123],"variational":[124],"minimize":[127],"functionals":[128],"Kullback-Leibler":[132],"(KL)":[133],"divergence.":[134],"LBP,":[135],"traditionally":[136],"developed":[137],"using":[138],"can":[141],"viewed":[144],"procedure.":[149],"We":[150,167],"applications":[155],"illustrating":[156],"use":[158],"effectiveness":[160],"algorithms":[164,189],"discussed":[165],"herein.":[166],"hope":[168],"by":[170],"reading":[171],"tutorial":[173],"readers":[175],"will":[176],"obtain":[177],"general":[179],"understanding":[180],"establish":[185],"among":[187],"popular":[188],"used":[190],"practice.":[192]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}