{"id":"https://openalex.org/W2009103630","doi":"https://doi.org/10.1109/icassp.2010.5496112","title":"Learning in Gaussian Markov random fields","display_name":"Learning in Gaussian Markov random fields","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2009103630","doi":"https://doi.org/10.1109/icassp.2010.5496112","mag":"2009103630"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2010.5496112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5496112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://infoscience.epfl.ch/record/143077","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000606323","display_name":"Thomas Riedl","orcid":"https://orcid.org/0000-0003-1084-316X"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Thomas J. Riedl","raw_affiliation_strings":["University of Illinois, Urbana-Champaign, USA","University of Illinois at Urbana\u2013Champaign, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana-Champaign, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"University of Illinois at Urbana\u2013Champaign, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028083945","display_name":"Andrew C. Singer","orcid":"https://orcid.org/0000-0001-9926-7036"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew C. Singer","raw_affiliation_strings":["University of Illinois, Urbana-Champaign, USA","University of Illinois at Urbana\u2013Champaign, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana-Champaign, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"University of Illinois at Urbana\u2013Champaign, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102839991","display_name":"Jun Won Choi","orcid":"https://orcid.org/0000-0002-3733-0148"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Won Choi","raw_affiliation_strings":["University of Illinois, Urbana-Champaign, USA","University of Illinois at Urbana\u2013Champaign, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana-Champaign, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"University of Illinois at Urbana\u2013Champaign, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000606323"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08907133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3070","last_page":"3073"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.995199978351593,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.995199978351593,"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9937000274658203,"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/parameterized-complexity","display_name":"Parameterized complexity","score":0.7984467148780823},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6575540900230408},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5845050811767578},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5804619193077087},{"id":"https://openalex.org/keywords/random-field","display_name":"Random field","score":0.5506640076637268},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5045453310012817},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5041199922561646},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.49300453066825867},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4909878075122833},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4625285267829895},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4369436800479889},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4341590404510498},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4330500364303589},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4166383147239685},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4006460905075073},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.397357314825058},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.39365246891975403},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3621804118156433},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35137560963630676},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24225518107414246},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16878989338874817},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09174081683158875}],"concepts":[{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.7984467148780823},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6575540900230408},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5845050811767578},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5804619193077087},{"id":"https://openalex.org/C130402806","wikidata":"https://www.wikidata.org/wiki/Q5361768","display_name":"Random field","level":2,"score":0.5506640076637268},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5045453310012817},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5041199922561646},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.49300453066825867},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4909878075122833},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4625285267829895},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4369436800479889},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4341590404510498},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4330500364303589},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4166383147239685},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4006460905075073},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.397357314825058},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.39365246891975403},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3621804118156433},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35137560963630676},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24225518107414246},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16878989338874817},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09174081683158875},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.0},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2010.5496112","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5496112","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:infoscience.tind.io:143077","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/143077","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference proceedings"}],"best_oa_location":{"id":"pmh:oai:infoscience.tind.io:143077","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/143077","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference proceedings"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1986466512","https://openalex.org/W2021380543","https://openalex.org/W2049633694","https://openalex.org/W2101030877","https://openalex.org/W2106233680","https://openalex.org/W2135328902","https://openalex.org/W2137813581","https://openalex.org/W2141451835","https://openalex.org/W2158122241","https://openalex.org/W2993880730","https://openalex.org/W3129711340","https://openalex.org/W6655646950","https://openalex.org/W6771505502"],"related_works":["https://openalex.org/W4387423321","https://openalex.org/W4233015508","https://openalex.org/W987019958","https://openalex.org/W2030382593","https://openalex.org/W1983122994","https://openalex.org/W2078379274","https://openalex.org/W2033503400","https://openalex.org/W2170151560","https://openalex.org/W2099971354","https://openalex.org/W2133071149"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,9,12,16,35,42,46,49,72,76],"problem":[4],"of":[5,15,48,75,97],"state":[6,36,50],"estimation":[7],"in":[8,31],"case":[10],"where":[11],"prior":[13,39,73],"distribution":[14,74],"states":[17,43,77],"is":[18,24,53,83,100],"not":[19],"perfectly":[20],"known":[21],"but":[22],"instead":[23],"parameterized":[25,65],"by":[26,103],"some":[27],"unknown":[28,58],"parameter.":[29],"Thus":[30],"order":[32],"to":[33,55,70,85],"support":[34],"estimator":[37],"with":[38],"information":[40],"on":[41,92],"and":[44,78],"improve":[45],"quality":[47],"estimates,":[51],"it":[52],"necessary":[54],"learn":[56,86],"this":[57,98],"parameter":[59],"first.":[60],"Here":[61],"we":[62],"assume":[63],"a":[64],"Gaussian":[66],"Markov":[67],"random":[68],"field":[69],"model":[71],"propose":[79],"an":[80],"algorithm":[81],"that":[82],"able":[84],"its":[87],"parameters":[88],"from":[89],"given":[90],"observations":[91],"these":[93],"states.":[94],"The":[95],"effectiveness":[96],"approach":[99],"proven":[101],"experimentally":[102],"simulations.":[104]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}