{"id":"https://openalex.org/W2124957271","doi":"https://doi.org/10.1109/mlsp.2012.6349812","title":"Pseudo inputs for pairwise learning with Gaussian processes","display_name":"Pseudo inputs for pairwise learning with Gaussian processes","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W2124957271","doi":"https://doi.org/10.1109/mlsp.2012.6349812","mag":"2124957271"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2012.6349812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2012.6349812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Workshop on Machine Learning for Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5110449958","display_name":"Jens Brehm Nielsen","orcid":null},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jens Brehm Nielsen","raw_affiliation_strings":["DTU Informatics, Technical University of Denmark, Kongens Lyngby, Denmark","DTU Informatics, Technical University of Denmark, Asmussens Alle B305, 2800 Kgs. Lyngby, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DTU Informatics, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]},{"raw_affiliation_string":"DTU Informatics, Technical University of Denmark, Asmussens Alle B305, 2800 Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048873240","display_name":"Bj\u00f8rn Sand Jensen","orcid":"https://orcid.org/0000-0001-8074-228X"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Bjorn Sand Jensen","raw_affiliation_strings":["DTU Informatics, Technical University of Denmark, Kongens Lyngby, Denmark","DTU Informatics, Technical University of Denmark, Asmussens Alle B305, 2800 Kgs. Lyngby, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DTU Informatics, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]},{"raw_affiliation_string":"DTU Informatics, Technical University of Denmark, Asmussens Alle B305, 2800 Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070673552","display_name":"Jan Larsen","orcid":"https://orcid.org/0000-0003-1880-1810"},"institutions":[{"id":"https://openalex.org/I96673099","display_name":"Technical University of Denmark","ror":"https://ror.org/04qtj9h94","country_code":"DK","type":"education","lineage":["https://openalex.org/I96673099"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jan Larsen","raw_affiliation_strings":["DTU Informatics, Technical University of Denmark, Kongens Lyngby, Denmark","DTU Informatics, Technical University of Denmark, Asmussens Alle B305, 2800 Kgs. Lyngby, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DTU Informatics, Technical University of Denmark, Kongens Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]},{"raw_affiliation_string":"DTU Informatics, Technical University of Denmark, Asmussens Alle B305, 2800 Kgs. Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96673099"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.19312141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"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/T11236","display_name":"Control Systems and Identification","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9753000140190125,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.7910816669464111},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6405842304229736},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6259495615959167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5245723724365234},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4774118661880493},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3761720657348633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33232226967811584},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06175258755683899}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7910816669464111},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6405842304229736},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6259495615959167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5245723724365234},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4774118661880493},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3761720657348633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33232226967811584},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06175258755683899},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/mlsp.2012.6349812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2012.6349812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Workshop on Machine Learning for Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.gla.ac.uk:119582","is_oa":false,"landing_page_url":"http://eprints.gla.ac.uk/119582/","pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"is_oa":false,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"},{"id":"pmh:oai:pure.atira.dk:publications/7bf11a71-3513-4bd1-a72b-cbcc61a2d17d","is_oa":false,"landing_page_url":"https://orbit.dtu.dk/en/publications/7bf11a71-3513-4bd1-a72b-cbcc61a2d17d","pdf_url":null,"source":{"id":"https://openalex.org/S4306400705","display_name":"Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I96673099","host_organization_name":"Technical University of Denmark","host_organization_lineage":["https://openalex.org/I96673099"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Nielsen , J B , Jensen , B S &amp; Larsen , J 2012 , Pseudo inputs for pairwise learning with Gaussian processes . in 2012 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) . IEEE , Machine Learning for Signal Processing , 2012 IEEE International Workshop on Machine Learning for Signal Processing , Santander , Spain , 23/10/2012 . https://doi.org/10.1109/MLSP.2012.6349812","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W42414577","https://openalex.org/W568924265","https://openalex.org/W1492761431","https://openalex.org/W1571870753","https://openalex.org/W1580216809","https://openalex.org/W1965520710","https://openalex.org/W1974160425","https://openalex.org/W2033442452","https://openalex.org/W2037679287","https://openalex.org/W2099768828","https://openalex.org/W2137956165","https://openalex.org/W2138481796","https://openalex.org/W2141570288","https://openalex.org/W2150905308","https://openalex.org/W2158139921","https://openalex.org/W4211049957","https://openalex.org/W4230646247","https://openalex.org/W6601679287","https://openalex.org/W6629473185","https://openalex.org/W6634689341","https://openalex.org/W6674989108","https://openalex.org/W6683338658","https://openalex.org/W6991122698","https://openalex.org/W7038339957"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W2556027894","https://openalex.org/W1964286703","https://openalex.org/W2169866437","https://openalex.org/W3056417032"],"abstract_inverted_index":{"We":[0],"consider":[1],"learning":[2],"and":[3,26,112,123,146,152],"prediction":[4],"of":[5,69,91,102,125],"pairwise":[6,20,35,46,94],"comparisons":[7,21],"between":[8],"instances.":[9],"The":[10,100],"problem":[11],"is":[12,41,106],"motivated":[13],"from":[14],"a":[15,44,51,87,109],"perceptual":[16],"view":[17],"point,":[18],"where":[19],"serve":[22],"as":[23,150],"an":[24,63],"effective":[25],"extensively":[27],"used":[28],"paradigm.":[29],"A":[30],"state-of-the-art":[31],"method":[32,60,77],"for":[33],"modeling":[34],"data":[36,116],"in":[37,67,141],"high":[38],"dimensional":[39],"domains":[40],"based":[42],"on":[43,108,113],"classical":[45,93],"probit":[47],"likelihood":[48,95],"imposed":[49],"with":[50,62],"Gaussian":[52,143],"process":[53,144],"prior.":[54],"While":[55],"extremely":[56],"flexible,":[57],"this":[58],"non-parametric":[59],"struggles":[61],"inconvenient":[64],"O(n3)":[65],"scaling":[66],"terms":[68],"the":[70,76,92,97,103,120,126,131],"n":[71],"input":[72],"instances":[73],"which":[74,118],"limits":[75],"only":[78],"to":[79,133],"smaller":[80],"problems.":[81],"To":[82],"overcome":[83],"this,":[84],"we":[85,129],"derive":[86],"specific":[88],"sparse":[89],"extension":[90,105],"using":[96],"pseudo-input":[98],"formulation.":[99],"behavior":[101],"proposed":[104],"demonstrated":[107],"toy":[110],"example":[111],"two":[114],"real-world":[115],"sets":[117],"outlines":[119],"potential":[121],"gain":[122],"pitfalls":[124],"approach.":[127],"Finally,":[128],"discuss":[130],"relation":[132],"other":[134],"similar":[135],"approximations":[136],"that":[137],"have":[138],"been":[139],"applied":[140],"standard":[142],"regression":[145],"classification":[147],"problems":[148],"such":[149],"FI(T)C":[151],"PI(T)C.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
