{"id":"https://openalex.org/W2023988209","doi":"https://doi.org/10.1109/cvpr.2011.5995522","title":"Supervised hypergraph labeling","display_name":"Supervised hypergraph labeling","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2023988209","doi":"https://doi.org/10.1109/cvpr.2011.5995522","mag":"2023988209"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2011.5995522","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995522","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","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/A5062468877","display_name":"Toufiq Parag","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163239","display_name":"Helix (United States)","ror":"https://ror.org/056jgxp12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210163239"]},{"id":"https://openalex.org/I195573530","display_name":"Janelia Research Campus","ror":"https://ror.org/013sk6x84","country_code":"US","type":"facility","lineage":["https://openalex.org/I1344073410","https://openalex.org/I195573530"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Toufiq Parag","raw_affiliation_strings":["Janelia Farm Research Campus, HHMI, Ashburn, VA, USA","Janelia Farm Research Campus, HHMI 19700 Helix Drive, Ashburn VA 20147"],"affiliations":[{"raw_affiliation_string":"Janelia Farm Research Campus, HHMI, Ashburn, VA, USA","institution_ids":["https://openalex.org/I195573530"]},{"raw_affiliation_string":"Janelia Farm Research Campus, HHMI 19700 Helix Drive, Ashburn VA 20147","institution_ids":["https://openalex.org/I195573530","https://openalex.org/I4210163239"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039640321","display_name":"Ahmed Elgammal","orcid":"https://orcid.org/0000-0003-2761-4822"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmed Elgammal","raw_affiliation_strings":["Department of Computer Science, Rutgers University, Piscataway, NJ, USA","Dept of Computer Science, Rutgers University, Piscataway, NJ 08854"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Rutgers University, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Dept of Computer Science, Rutgers University, Piscataway, NJ 08854","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062468877"],"corresponding_institution_ids":["https://openalex.org/I195573530","https://openalex.org/I4210163239"],"apc_list":null,"apc_paid":null,"fwci":0.312,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.53959269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"2289","last_page":"2296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9968000054359436,"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/T11106","display_name":"Data Management and Algorithms","score":0.9968000054359436,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9837999939918518,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9832000136375427,"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/hypergraph","display_name":"Hypergraph","score":0.842890739440918},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7904955744743347},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6342887282371521},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.555080771446228},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.5342843532562256},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.48385488986968994},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.48226457834243774},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4596732258796692},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4152156114578247},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35312557220458984},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2978786826133728},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2577461004257202},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.14369988441467285}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.842890739440918},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7904955744743347},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6342887282371521},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.555080771446228},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.5342843532562256},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.48385488986968994},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48226457834243774},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4596732258796692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4152156114578247},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35312557220458984},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2978786826133728},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2577461004257202},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.14369988441467285},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2011.5995522","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995522","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.221.6214","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.6214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.rutgers.edu/%7Eelgammal/pub/CVPR11_Parag.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W59895198","https://openalex.org/W118408326","https://openalex.org/W1651266332","https://openalex.org/W2005103485","https://openalex.org/W2020999234","https://openalex.org/W2024548552","https://openalex.org/W2083637347","https://openalex.org/W2085261163","https://openalex.org/W2103498186","https://openalex.org/W2107884096","https://openalex.org/W2113339916","https://openalex.org/W2119947613","https://openalex.org/W2121845348","https://openalex.org/W2124583124","https://openalex.org/W2128680590","https://openalex.org/W2135165032","https://openalex.org/W2135414191","https://openalex.org/W2137813581","https://openalex.org/W2150024778","https://openalex.org/W2158579916","https://openalex.org/W2161567010","https://openalex.org/W2171675680","https://openalex.org/W2189543453","https://openalex.org/W2236614481","https://openalex.org/W3000400585","https://openalex.org/W6604822289","https://openalex.org/W6677988828","https://openalex.org/W6678680863","https://openalex.org/W6682133467"],"related_works":["https://openalex.org/W2776613281","https://openalex.org/W2962950510","https://openalex.org/W4226287370","https://openalex.org/W2114556850","https://openalex.org/W2153267847","https://openalex.org/W3021913283","https://openalex.org/W2159992248","https://openalex.org/W4297812452","https://openalex.org/W959529772","https://openalex.org/W2070797946"],"abstract_inverted_index":{"We":[0,67,109],"address":[1],"the":[2,26,54,74,84,96,111,120,152],"problem":[3,39,45,85],"of":[4,16,86,101,113,119,142,151],"labeling":[5,44,88],"individual":[6],"datapoints":[7],"given":[8],"some":[9],"knowledge":[10,19],"about":[11],"(small)":[12],"subsets":[13],"or":[14],"groups":[15],"them.":[17],"The":[18],"we":[20],"have":[21,138],"for":[22,29,126],"a":[23,35,51,59,69],"group":[24,31],"is":[25,40,134],"likelihood":[27,62],"value":[28,63],"each":[30,47,55],"member":[32],"to":[33,42,50,58,72,137],"satisfy":[34],"certain":[36],"model.":[37],"This":[38,93],"equivalent":[41],"hypergraph":[43,87],"where":[46],"datapoint":[48],"corresponds":[49],"node":[52],"and":[53,82,98,104,128],"subset":[56],"correspond":[57],"hyperedge":[60],"with":[61,116],"as":[64,149],"its":[65],"weight.":[66],"propose":[68],"novel":[70],"method":[71],"model":[73,103],"label":[75],"dependence":[76],"using":[77],"an":[78,90],"Undirected":[79],"Graphical":[80],"Model":[81],"reduce":[83],"into":[89],"inference":[91,127],"problem.":[92],"paper":[94],"describes":[95],"structure":[97],"necessary":[99],"components":[100],"such":[102],"proposes":[105],"useful":[106],"cost":[107,121],"functions.":[108],"discuss":[110],"behavior":[112],"proposed":[114,153],"algorithm":[115],"different":[117],"forms":[118],"functions,":[122],"identify":[123],"suitable":[124],"algorithms":[125],"analyze":[129],"required":[130],"properties":[131],"when":[132],"it":[133],"theoretically":[135],"guaranteed":[136],"exact":[139],"solution.":[140],"Examples":[141],"several":[143],"real":[144],"world":[145],"problems":[146],"are":[147],"shown":[148],"applications":[150],"method.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
