{"id":"https://openalex.org/W2401540776","doi":null,"title":"Bayesian supervised dictionary learning","display_name":"Bayesian supervised dictionary learning","publication_year":2013,"publication_date":"2013-07-15","ids":{"openalex":"https://openalex.org/W2401540776","mag":"2401540776"},"language":"en","primary_location":{"id":"mag:2401540776","doi":null,"is_oa":false,"landing_page_url":"http://ceur-ws.org/Vol-1024/paper-02.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5026657271","display_name":"Behnam Babagholami-Mohamadabadi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Behnam Babagholami-Mohamadabadi","raw_affiliation_strings":["CE Dept., Sharif University, Tehran, Iran#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CE Dept., Sharif University, Tehran, Iran#TAB#","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063037457","display_name":"Amin Jourabloo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Amin Jourabloo","raw_affiliation_strings":["CE Dept., Sharif University, Tehran, Iran#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CE Dept., Sharif University, Tehran, Iran#TAB#","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045033461","display_name":"Mohammadreza Zolfaghari","orcid":"https://orcid.org/0000-0002-2973-4302","observed_orcids":["https://orcid.org/0000-0002-2973-4302"]},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammadreza Zolfaghari","raw_affiliation_strings":["CE Dept., Sharif University, Tehran, Iran#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-2973-4302","affiliations":[{"raw_affiliation_string":"CE Dept., Sharif University, Tehran, Iran#TAB#","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081696451","display_name":"Mohammad Taghi Manzuri","orcid":"https://orcid.org/0000-0002-3451-0338","observed_orcids":["https://orcid.org/0000-0002-3451-0338"]},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mohammad Taghi Manzuri","raw_affiliation_strings":["CE Dept., Sharif University, Tehran, Iran#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-3451-0338","affiliations":[{"raw_affiliation_string":"CE Dept., Sharif University, Tehran, Iran#TAB#","institution_ids":["https://openalex.org/I133529467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I133529467"],"apc_list":null,"apc_paid":null,"fwci":0.7247,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74307054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"11","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.48510000109672546,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.48510000109672546,"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/T10057","display_name":"Face and Expression Recognition","score":0.07649999856948853,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.03929999843239784,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"dictionary learning","score":0.8989999890327454},{"id":"https://openalex.org/keywords/sparse-coding","display_name":"sparse coding","score":0.777999997138977},{"id":"https://openalex.org/keywords/non-parametric-bayesian-inference","display_name":"non-parametric Bayesian inference","score":0.7059999704360962},{"id":"https://openalex.org/keywords/variational-bayesian-inference","display_name":"variational inference","score":0.7009999752044678},{"id":"https://openalex.org/keywords/classification","display_name":"classification","score":0.3149999976158142},{"id":"https://openalex.org/keywords/posterior-estimation","display_name":"posterior distribution estimation","score":0.6039999723434448},{"id":"https://openalex.org/keywords/limited-training-data","display_name":"limited training data","score":0.6330000162124634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6522033214569092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6439056992530823},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5660735964775085},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5641824007034302},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5278869867324829},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.523037314414978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5186328291893005},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4600408673286438},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.4549512267112732},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.42773425579071045},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.2827799916267395},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0852014422416687}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2401540776","doi":null,"is_oa":false,"landing_page_url":"http://ceur-ws.org/Vol-1024/paper-02.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W130710483","https://openalex.org/W1496451467","https://openalex.org/W1517266559","https://openalex.org/W1522547150","https://openalex.org/W1591385104","https://openalex.org/W1985093013","https://openalex.org/W1987532879","https://openalex.org/W1992405901","https://openalex.org/W2027805700","https://openalex.org/W2032768707","https://openalex.org/W2069959554","https://openalex.org/W2084812512","https://openalex.org/W2100659887","https://openalex.org/W2112796928","https://openalex.org/W2115979064","https://openalex.org/W2117111086","https://openalex.org/W2125874614","https://openalex.org/W2128638419","https://openalex.org/W2129812935","https://openalex.org/W2138451337","https://openalex.org/W2140433132","https://openalex.org/W2146047955","https://openalex.org/W2157785665","https://openalex.org/W2160547390","https://openalex.org/W2994340921"],"related_works":["https://openalex.org/W7095528248","https://openalex.org/W2254969944","https://openalex.org/W4394658277","https://openalex.org/W2023646202","https://openalex.org/W2101381488","https://openalex.org/W4285211004","https://openalex.org/W32302860","https://openalex.org/W4390411507","https://openalex.org/W2145645607","https://openalex.org/W6941418456"],"abstract_inverted_index":{"This":[0,66],"paper":[1,67],"proposes":[2],"a":[3,69,78,97],"novel":[4],"Bayesian":[5,21,70],"method":[6],"for":[7,72,81],"the":[8,26,29,32,45,47,51,59,82,85,88,104,108,112,127],"dictionary":[9],"learning":[10],"(DL)":[11],"based":[12,37,74,137],"classification":[13,38,75,124,132,138],"using":[14],"Beta-Bernoulli":[15],"process.":[16],"We":[17,94],"utilize":[18],"this":[19],"non-parametric":[20],"technique":[22],"to":[23,102,115,118],"learn":[24],"jointly":[25],"sparse":[27,48,83],"codes,":[28,49,84],"dictionary,":[30,46,86],"and":[31,50,53,87],"classifier":[33,52,89],"together.":[34],"Existing":[35],"DL":[36,73,136],"approaches":[39],"only":[40],"offer":[41],"point":[42],"estimation":[43],"of":[44,61,107],"can":[54],"therefore":[55],"be":[56,116],"unreliable":[57],"when":[58],"number":[60],"training":[62,92],"examples":[63],"is":[64],"small.":[65],"presents":[68],"framework":[71,129],"that":[76,126],"estimates":[77],"posterior":[79,105],"distribution":[80,106],"from":[90],"labeled":[91],"data.":[93],"also":[95],"develop":[96],"Variational":[98],"Bayes":[99],"(VB)":[100],"algorithm":[101],"compute":[103],"parameters":[109],"which":[110],"allows":[111],"proposed":[113,128],"model":[114],"applicable":[117],"large":[119],"scale":[120],"datasets.":[121],"Experiments":[122],"in":[123],"demonstrate":[125],"achieves":[130],"higher":[131],"accuracy":[133],"than":[134],"state-of-the-art":[135],"algorithms.":[139]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2026-09-26T08:19:03.415552","created_date":"2016-06-24T00:00:00"}
