{"id":"https://openalex.org/W2916718974","doi":"https://doi.org/10.1109/icpr.2018.8545302","title":"Variational Bayes Block Sparse Modeling with Correlated Entries","display_name":"Variational Bayes Block Sparse Modeling with Correlated Entries","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2916718974","doi":"https://doi.org/10.1109/icpr.2018.8545302","mag":"2916718974"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5001956353","display_name":"Shruti Sharma","orcid":"https://orcid.org/0000-0002-7610-4856"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shruti Sharma","raw_affiliation_strings":["Dept. of Electrical Engg., IIT, Delhi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engg., IIT, Delhi","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086242686","display_name":"Santanu Chaudhury","orcid":"https://orcid.org/0000-0002-5488-7773"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Santanu Chaudhury","raw_affiliation_strings":["Dept. of Electrical Engg., IIT, Delhi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engg., IIT, Delhi","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002842122","display_name":"Jayadeva","orcid":null},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jayadeva","raw_affiliation_strings":["IIT, Dept. of Electrical Engg., Delhi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT, Dept. of Electrical Engg., Delhi","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.1804,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.4359369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1313","last_page":"1318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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":0.9990000128746033,"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"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9983999729156494,"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/block","display_name":"Block (permutation group theory)","score":0.6871639490127563},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6669801473617554},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.6368768215179443},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.6283708810806274},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6267129182815552},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6189371943473816},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5602155327796936},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45222100615501404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4505850672721863},{"id":"https://openalex.org/keywords/bayes-estimator","display_name":"Bayes estimator","score":0.43049243092536926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4297259449958801},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35342079401016235},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24271130561828613}],"concepts":[{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6871639490127563},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6669801473617554},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.6368768215179443},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.6283708810806274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6267129182815552},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6189371943473816},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5602155327796936},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45222100615501404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4505850672721863},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.43049243092536926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4297259449958801},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35342079401016235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24271130561828613},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W866015105","https://openalex.org/W1607198972","https://openalex.org/W1663973292","https://openalex.org/W1723619723","https://openalex.org/W1987415890","https://openalex.org/W2033419225","https://openalex.org/W2111414067","https://openalex.org/W2130836991","https://openalex.org/W2136870201","https://openalex.org/W2141224535","https://openalex.org/W2152279006","https://openalex.org/W2164129707","https://openalex.org/W2244252827","https://openalex.org/W2326423284","https://openalex.org/W2594551469","https://openalex.org/W3005708632","https://openalex.org/W3140968660","https://openalex.org/W6629510986"],"related_works":["https://openalex.org/W2343819364","https://openalex.org/W2133205540","https://openalex.org/W2562263695","https://openalex.org/W2015518264","https://openalex.org/W2147201983","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W1718066205","https://openalex.org/W2793406240","https://openalex.org/W2135187896"],"abstract_inverted_index":{"This":[0,55],"paper":[1,56],"addresses":[2],"the":[3,13,20,31,59,67,97,101,119],"problem":[4],"of":[5,66,100,106,121,126],"Bayesian":[6,53,71],"Block":[7,69],"Sparse":[8,70],"Modeling":[9],"when":[10],"coefficients":[11],"within":[12,30],"blocks":[14],"are":[15,94],"correlated.":[16],"In":[17],"contrast":[18],"to":[19,112],"current":[21],"hierarchical":[22,38],"methods":[23,74,80],"which":[24],"do":[25],"not":[26],"exploit":[27],"correlation":[28],"structure":[29],"blocks,":[32],"we":[33],"propose":[34],"a":[35,114],"three":[36],"level":[37],"estimation":[39],"framework.":[40],"It":[41],"employs":[42],"heavy-tailed":[43],"priors":[44],"for":[45,52,91],"block":[46],"sparse":[47],"modeling":[48],"and":[49,64,75],"variational":[50],"inference":[51],"estimation.":[54],"also":[57,117],"describes":[58],"relationship":[60],"between":[61],"proposed":[62,102],"framework":[63,103,123],"some":[65],"existing":[68],"Learning":[72],"(SBL)":[73],"show":[76],"that":[77],"these":[78],"SBL":[79],"can":[81],"be":[82],"viewed":[83],"as":[84],"its":[85],"special":[86],"cases.":[87],"Extensive":[88],"experimental":[89],"results":[90],"synthetic":[92],"signals":[93],"provided,":[95],"demonstrating":[96],"superior":[98],"performance":[99],"in":[104,124],"terms":[105],"failure":[107],"rate,":[108],"relative":[109],"reconstruction":[110],"error,":[111],"name":[113],"few.":[115],"We":[116],"demonstrate":[118],"applicability":[120],"this":[122],"telemonitoring":[125],"Fetal":[127],"Electrocardiogram.":[128]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
