{"id":"https://openalex.org/W2040747066","doi":"https://doi.org/10.1109/cvpr.2009.5206650","title":"Alphabet SOUP: A framework for approximate energy minimization","display_name":"Alphabet SOUP: A framework for approximate energy minimization","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2040747066","doi":"https://doi.org/10.1109/cvpr.2009.5206650","mag":"2040747066"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206650","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","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/A5071663279","display_name":"Stephen Jay Gould","orcid":"https://orcid.org/0000-0001-8929-7899"},"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":true,"raw_author_name":"Stephen Gould","raw_affiliation_strings":["Department of Electrical Engineering, University of Stanford, USA","[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019619921","display_name":"Fernando Amat","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":"Fernando Amat","raw_affiliation_strings":["Department of Electrical Engineering, University of Stanford, USA","[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]","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":["Department of Electrical Engineering, University of Stanford, USA","[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071663279"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":2.115,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.88868941,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"903","last_page":"910"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9976999759674072,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9955999851226807,"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/belief-propagation","display_name":"Belief propagation","score":0.7294825315475464},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.6858072280883789},{"id":"https://openalex.org/keywords/alphabet","display_name":"Alphabet","score":0.637462854385376},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.5745851993560791},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5288734436035156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.526591956615448},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.522351861000061},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49175146222114563},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47300654649734497},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4725361168384552},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4507366418838501},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.44996824860572815},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.43050599098205566},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.42215609550476074},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33369699120521545},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3024657368659973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23816132545471191},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11295917630195618},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09232813119888306}],"concepts":[{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.7294825315475464},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.6858072280883789},{"id":"https://openalex.org/C112876837","wikidata":"https://www.wikidata.org/wiki/Q837518","display_name":"Alphabet","level":2,"score":0.637462854385376},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.5745851993560791},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5288734436035156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.526591956615448},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.522351861000061},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49175146222114563},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47300654649734497},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4725361168384552},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4507366418838501},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.44996824860572815},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.43050599098205566},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.42215609550476074},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33369699120521545},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3024657368659973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23816132545471191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11295917630195618},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09232813119888306},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2009.5206650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206650","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.160.1902","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.160.1902","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/Gould+al:CVPR09.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.296.725","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.296.725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://users.cecs.anu.edu.au/~sgould/papers/cvpr09-errata.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W79315950","https://openalex.org/W1513861746","https://openalex.org/W1563007904","https://openalex.org/W1579186192","https://openalex.org/W1601035521","https://openalex.org/W1978493028","https://openalex.org/W1980604167","https://openalex.org/W2015447696","https://openalex.org/W2022552785","https://openalex.org/W2081351607","https://openalex.org/W2101309634","https://openalex.org/W2103380420","https://openalex.org/W2107884096","https://openalex.org/W2108619558","https://openalex.org/W2110306576","https://openalex.org/W2114741181","https://openalex.org/W2116877738","https://openalex.org/W2121845348","https://openalex.org/W2125873654","https://openalex.org/W2128962821","https://openalex.org/W2135165032","https://openalex.org/W2137117160","https://openalex.org/W2143524933","https://openalex.org/W2146036075","https://openalex.org/W2147880316","https://openalex.org/W2148852318","https://openalex.org/W2149474573","https://openalex.org/W2153396823","https://openalex.org/W2157394577","https://openalex.org/W2164918853","https://openalex.org/W3004177386","https://openalex.org/W4250143236","https://openalex.org/W4252621450","https://openalex.org/W6636093472","https://openalex.org/W6645069844","https://openalex.org/W6671016552","https://openalex.org/W6677988828","https://openalex.org/W6681421934","https://openalex.org/W6682082992","https://openalex.org/W6682467843"],"related_works":["https://openalex.org/W2396038226","https://openalex.org/W2169282664","https://openalex.org/W2097090565","https://openalex.org/W2151646056","https://openalex.org/W2008444830","https://openalex.org/W185838248","https://openalex.org/W50065450","https://openalex.org/W2804375118","https://openalex.org/W2143052184","https://openalex.org/W2180905035"],"abstract_inverted_index":{"Many":[0],"problems":[1,53],"in":[2,22,29],"computer":[3],"vision":[4,159],"can":[5],"be":[6],"modeled":[7],"using":[8],"conditional":[9],"Markov":[10],"random":[11],"fields":[12],"(CRF).":[13],"Since":[14],"finding":[15,36,84],"the":[16,72,123,126,129,145],"maximum":[17],"a":[18,80,104,114,119,155],"posteriori":[19],"(MAP)":[20],"solution":[21,127],"such":[23,45,65],"models":[24],"is":[25,135],"NP-hard,":[26],"much":[27],"attention":[28],"recent":[30],"years":[31],"has":[32],"been":[33],"placed":[34],"on":[35,122],"good":[37],"approximate":[38,85],"solutions.":[39],"In":[40,75],"particular,":[41],"graph-cut":[42],"based":[43],"algorithms,":[44,64],"as":[46,66],"a-expansion,":[47],"are":[48,70],"tremendously":[49],"successful":[50],"at":[51],"solving":[52,111],"with":[54],"regular":[55],"potentials.":[56],"However,":[57],"for":[58,83,97,100,154],"arbitrary":[59,89],"energy":[60,90,152],"functions,":[61],"message":[62],"passing":[63],"max-product":[67],"belief":[68],"propagation,":[69],"still":[71],"only":[73],"resort.":[74],"this":[76,141],"paper":[77],"we":[78],"describe":[79],"general":[81],"framework":[82],"MAP":[86],"solutions":[87,153],"of":[88,125,132,147,158],"functions.":[91],"Our":[92],"algorithm":[93,134],"(called":[94],"Alphabet":[95],"SOUP":[96],"Sequential":[98],"Optimization":[99],"Unrestricted":[101],"Potentials)":[102],"performs":[103],"search":[105],"over":[106,113],"variable":[107],"assignments":[108],"by":[109],"iteratively":[110],"subproblems":[112],"reduced":[115],"state-space.":[116],"We":[117,138],"provide":[118],"theoretical":[120],"guarantee":[121],"quality":[124],"when":[128],"inner":[130],"loop":[131],"our":[133],"solved":[136],"exactly.":[137],"show":[139],"that":[140],"approach":[142],"greatly":[143],"improves":[144],"efficiency":[146],"inference":[148],"and":[149],"achieves":[150],"lower":[151],"broad":[156],"range":[157],"problems.":[160]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
