{"id":"https://openalex.org/W2002806284","doi":"https://doi.org/10.1145/1015330.1015337","title":"Kernel conditional random fields","display_name":"Kernel conditional random fields","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2002806284","doi":"https://doi.org/10.1145/1015330.1015337","mag":"2002806284"},"language":"en","primary_location":{"id":"doi:10.1145/1015330.1015337","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015337","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/A5060219657","display_name":"John Lafferty","orcid":"https://orcid.org/0000-0002-5929-220X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"John Lafferty","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA","Carnegie-Mellon University, Pittsburgh, PA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103428074","display_name":"Xiaojin Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaojin Zhu","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA","Carnegie-Mellon University, Pittsburgh, PA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351175","display_name":"Yan Liu","orcid":"https://orcid.org/0000-0003-4242-4840"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA","Carnegie-Mellon University, Pittsburgh, PA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060219657"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":4.0998,"has_fulltext":false,"cited_by_count":124,"citation_normalized_percentile":{"value":0.9459576,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"64","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9941999912261963,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.8449336290359497},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7555332183837891},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.6090589761734009},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5928344130516052},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5781304836273193},{"id":"https://openalex.org/keywords/graph-kernel","display_name":"Graph kernel","score":0.5282769799232483},{"id":"https://openalex.org/keywords/clique","display_name":"Clique","score":0.4687870740890503},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4623365104198456},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43537232279777527},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43349310755729675},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42649421095848083},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.4107629954814911},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39093536138534546},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3697185516357422},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3498457074165344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.342949241399765},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3008384704589844},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.1556820571422577},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09581547975540161}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8449336290359497},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7555332183837891},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.6090589761734009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5928344130516052},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5781304836273193},{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.5282769799232483},{"id":"https://openalex.org/C2777035058","wikidata":"https://www.wikidata.org/wiki/Q1662634","display_name":"Clique","level":2,"score":0.4687870740890503},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4623365104198456},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43537232279777527},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43349310755729675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42649421095848083},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.4107629954814911},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39093536138534546},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3697185516357422},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3498457074165344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.342949241399765},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3008384704589844},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.1556820571422577},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09581547975540161}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1015330.1015337","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015337","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7699999809265137}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1774304772","https://openalex.org/W1966949944","https://openalex.org/W2008652694","https://openalex.org/W2008708467","https://openalex.org/W2034797903","https://openalex.org/W2096071754","https://openalex.org/W2100890997","https://openalex.org/W2104972430","https://openalex.org/W2105644991","https://openalex.org/W2107008379","https://openalex.org/W2113592823","https://openalex.org/W2114229504","https://openalex.org/W2139193890","https://openalex.org/W2139686264","https://openalex.org/W2139823104","https://openalex.org/W2145295623","https://openalex.org/W2147880316","https://openalex.org/W2149684865","https://openalex.org/W2153187042","https://openalex.org/W2156515921","https://openalex.org/W2160842254"],"related_works":["https://openalex.org/W2574115973","https://openalex.org/W2119772606","https://openalex.org/W2604913466","https://openalex.org/W2189183545","https://openalex.org/W2153211825","https://openalex.org/W4300454542","https://openalex.org/W2122054752","https://openalex.org/W3008135798","https://openalex.org/W1028655896","https://openalex.org/W2002806284"],"abstract_inverted_index":{"Kernel":[0],"conditional":[1,20,29,69],"random":[2,30],"fields":[3,31],"(KCRFs)":[4],"are":[5,93,100],"introduced":[6],"as":[7],"a":[8],"framework":[9,73,88],"for":[10,19,46,78],"discriminative":[11],"modeling":[12],"of":[13,84,106],"graph-structured":[14],"data.":[15],"A":[16,44],"representer":[17],"theorem":[18],"graphical":[21,70],"models":[22],"is":[23,54],"given":[24],"which":[25,57],"shows":[26],"how":[27],"kernel":[28],"arise":[32],"from":[33],"risk":[34],"minimization":[35],"procedures":[36],"defined":[37],"using":[38],"Mercer":[39],"kernels":[40,63],"on":[41],"labeled":[42],"graphs.":[43],"procedure":[45],"greedily":[47],"selecting":[48],"cliques":[49],"in":[50,95],"the":[51,72,82,104],"dual":[52],"representation":[53],"then":[55],"proposed,":[56],"allows":[58],"sparse":[59],"representations.":[60],"By":[61],"incorporating":[62],"and":[64,89,99],"implicit":[65],"feature":[66],"spaces":[67],"into":[68],"models,":[71],"enables":[74],"semi-supervised":[75],"learning":[76],"algorithms":[77],"structured":[79],"data":[80,97],"through":[81],"use":[83],"graph":[85],"kernels.":[86],"The":[87],"clique":[90],"selection":[91],"methods":[92],"demonstrated":[94],"synthetic":[96],"experiments,":[98],"also":[101],"applied":[102],"to":[103],"problem":[105],"protein":[107],"secondary":[108],"structure":[109],"prediction.":[110]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
