{"id":"https://openalex.org/W2106122512","doi":"https://doi.org/10.1145/1015330.1015444","title":"Learning associative Markov networks","display_name":"Learning associative Markov networks","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2106122512","doi":"https://doi.org/10.1145/1015330.1015444","mag":"2106122512"},"language":"en","primary_location":{"id":"doi:10.1145/1015330.1015444","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning  - ICML '04","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/A5111908443","display_name":"Ben Taskar","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ben Taskar","raw_affiliation_strings":["Stanford University, Stanford, CA","Stanford University Stanford CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University Stanford CA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042574866","display_name":"Vassil Chatalbashev","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vassil Chatalbashev","raw_affiliation_strings":["Stanford University, Stanford, CA","Stanford University Stanford CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University Stanford CA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051658526","display_name":"Daphne Koller","orcid":"https://orcid.org/0000-0002-2361-6479"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daphne Koller","raw_affiliation_strings":["Stanford University, Stanford, CA","Stanford University Stanford CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University Stanford CA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":11.5636,"has_fulltext":false,"cited_by_count":176,"citation_normalized_percentile":{"value":0.98398986,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"102","last_page":"102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9993000030517578,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9993000030517578,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9987000226974487,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9987000226974487,"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/markov-blanket","display_name":"Markov blanket","score":0.6806929111480713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6776317358016968},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6555171012878418},{"id":"https://openalex.org/keywords/clique","display_name":"Clique","score":0.6286213994026184},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.51987624168396},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4951151907444},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.48077529668807983},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.4732440412044525},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.4608099162578583},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.4519290328025818},{"id":"https://openalex.org/keywords/associative-property","display_name":"Associative property","score":0.4509262442588806},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4482826292514801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4169911742210388},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.40092459321022034},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3311096429824829},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3295811414718628},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2682231366634369}],"concepts":[{"id":"https://openalex.org/C123867240","wikidata":"https://www.wikidata.org/wiki/Q3001792","display_name":"Markov blanket","level":5,"score":0.6806929111480713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6776317358016968},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6555171012878418},{"id":"https://openalex.org/C2777035058","wikidata":"https://www.wikidata.org/wiki/Q1662634","display_name":"Clique","level":2,"score":0.6286213994026184},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.51987624168396},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4951151907444},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.48077529668807983},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.4732440412044525},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.4608099162578583},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.4519290328025818},{"id":"https://openalex.org/C159423971","wikidata":"https://www.wikidata.org/wiki/Q177251","display_name":"Associative property","level":2,"score":0.4509262442588806},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4482826292514801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4169911742210388},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.40092459321022034},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3311096429824829},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3295811414718628},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2682231366634369},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1145/1015330.1015444","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning  - ICML '04","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1.7949","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.7949","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aicml.cs.ualberta.ca/banff04/icml/pages/papers/394.ps","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.123.4359","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.4359","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ai.stanford.edu/~koller/Papers/Taskar+al:ICML04.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.157.329","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cis.upenn.edu/~taskar/pubs/mmamn.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.71.8512","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.71.8512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://kingman.cs.ualberta.ca/_banff04/icml/pages/papers/394.ps","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.91.1321","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.1321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ai.stanford.edu/~vasco/pubs/mmamn.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W79315950","https://openalex.org/W1554544485","https://openalex.org/W1762430620","https://openalex.org/W2011986160","https://openalex.org/W2061130579","https://openalex.org/W2072640386","https://openalex.org/W2076008912","https://openalex.org/W2096139825","https://openalex.org/W2098678088","https://openalex.org/W2101309634","https://openalex.org/W2101897555","https://openalex.org/W2105644991","https://openalex.org/W2108619558","https://openalex.org/W2134125014","https://openalex.org/W2142241599","https://openalex.org/W2143516773","https://openalex.org/W2147880316","https://openalex.org/W2159793005","https://openalex.org/W2167044614","https://openalex.org/W2962735828"],"related_works":["https://openalex.org/W1985664346","https://openalex.org/W2386792210","https://openalex.org/W2130519334","https://openalex.org/W2118728396","https://openalex.org/W2382132287","https://openalex.org/W3164302780","https://openalex.org/W3113307220","https://openalex.org/W2970110578","https://openalex.org/W23237351","https://openalex.org/W1983169436"],"abstract_inverted_index":{"Markov":[0,31,50,141,148,164],"networks":[1,32,61,84,165],"are":[2,53],"extensively":[3],"used":[4],"to":[5,103,158],"model":[6],"complex":[7],"sequential,":[8],"spatial,":[9],"and":[10,23,27,69,189],"relational":[11],"interactions":[12],"in":[13,29,80,94,97,124,183],"fields":[14],"as":[15,17],"diverse":[16],"image":[18],"processing,":[19],"natural":[20],"language":[21],"analysis,":[22],"bioinformatics.":[24],"However,":[25],"inference":[26],"learning":[28,41,138],"general":[30],"is":[33,156,174],"intractable.":[34],"In":[35],"this":[36,153],"paper,":[37],"we":[38],"focus":[39],"on":[40],"a":[42,111,139],"large":[43],"subclass":[44,59],"of":[45,62,91,118,137,166],"such":[46,125],"models":[47],"(called":[48],"associative":[49,147],"networks)":[51],"that":[52,72,145],"tractable":[54],"or":[55],"closely":[56],"approximable.":[57],"This":[58],"contains":[60],"discrete":[63],"variables":[64,79,101],"with":[65,187],"K":[66],"labels":[67,76],"each":[68],"clique":[70],"potentials":[71],"favor":[73],"the":[74,81,86,105,116,120,135,170,178],"same":[75,106],"for":[77,115,134,146,163],"all":[78],"clique.":[82],"Such":[83],"capture":[85],"\"guilt":[87],"by":[88],"association\"":[89],"pattern":[90],"reasoning":[92],"present":[93],"many":[95],"domains,":[96],"which":[98,127],"connected":[99],"(\"associated\")":[100],"tend":[102],"have":[104],"label.":[107],"Our":[108],"approach":[109],"exploits":[110],"linear":[112],"programming":[113],"relaxation":[114,179],"task":[117],"finding":[119],"best":[121],"joint":[122],"assignment":[123],"networks,":[126],"provides":[128],"an":[129,160],"approximate":[130,154],"quadratic":[131],"program":[132],"(QP)":[133],"problem":[136],"margin-maximizing":[140],"network.":[142],"We":[143],"show":[144,192],"network":[149],"over":[150,195],"binary-valued":[151],"variables,":[152],"QP":[155],"guaranteed":[157],"return":[159],"optimal":[161],"parameterization":[162],"arbitrary":[167],"topology.":[168],"For":[169],"nonbinary":[171],"case,":[172],"optimality":[173],"not":[175],"guaranteed,":[176],"but":[177],"produces":[180],"good":[181],"solutions":[182],"practice.":[184],"Experimental":[185],"results":[186],"hypertext":[188],"newswire":[190],"classification":[191],"significant":[193],"advantages":[194],"standard":[196],"approaches.":[197]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":22}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
