{"id":"https://openalex.org/W2163203678","doi":"https://doi.org/10.1109/tnn.2011.2168568","title":"Bayesian Multitask Classification With Gaussian Process Priors","display_name":"Bayesian Multitask Classification With Gaussian Process Priors","publication_year":2011,"publication_date":"2011-10-12","ids":{"openalex":"https://openalex.org/W2163203678","doi":"https://doi.org/10.1109/tnn.2011.2168568","mag":"2163203678","pmid":"https://pubmed.ncbi.nlm.nih.gov/21990334"},"language":"en","primary_location":{"id":"doi:10.1109/tnn.2011.2168568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnn.2011.2168568","pdf_url":null,"source":{"id":"https://openalex.org/S42080949","display_name":"IEEE Transactions on Neural Networks","issn_l":"1045-9227","issn":["1045-9227","1941-0093"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5013838849","display_name":"Grigorios Skolidis","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"G. Skolidis","raw_affiliation_strings":["School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK. G.skolidis@sms.ed.ac.uk"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK. G.skolidis@sms.ed.ac.uk","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017674487","display_name":"Guido Sanguinetti","orcid":"https://orcid.org/0000-0002-6663-8336"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"G. Sanguinetti","raw_affiliation_strings":["School of Informatics, University of Edinburgh, Edinburgh, UK","Sch. of Inf., Univ. of Edinburgh, Edinburgh, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics, University of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"Sch. of Inf., Univ. of Edinburgh, Edinburgh, UK","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98677209"],"apc_list":null,"apc_paid":null,"fwci":10.5341,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.98140608,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"22","issue":"12","first_page":"2011","last_page":"2021"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9742000102996826,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9678000211715698,"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/computer-science","display_name":"Computer science","score":0.7089787721633911},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.685073971748352},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6702468991279602},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6612468957901001},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.6453285813331604},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5282819867134094},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5199783444404602},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.48361149430274963},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.45598816871643066},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45421209931373596},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.43336474895477295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41078606247901917},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.2717857360839844},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.22243958711624146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1970238983631134},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13688483834266663}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7089787721633911},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.685073971748352},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6702468991279602},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6612468957901001},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.6453285813331604},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5282819867134094},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5199783444404602},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.48361149430274963},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.45598816871643066},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45421209931373596},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.43336474895477295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41078606247901917},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2717857360839844},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.22243958711624146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1970238983631134},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13688483834266663},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tnn.2011.2168568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnn.2011.2168568","pdf_url":null,"source":{"id":"https://openalex.org/S42080949","display_name":"IEEE Transactions on Neural Networks","issn_l":"1045-9227","issn":["1045-9227","1941-0093"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks","raw_type":"journal-article"},{"id":"pmid:21990334","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/21990334","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks","raw_type":null},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1375452","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1375452/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Neural Netw , 22 (12) pp. 2011-2021. (2011)","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1256035484","display_name":null,"funder_award_id":"EP/F009461/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3408079372","display_name":"Advancing Machine Learning Methodology for New Classes of Prediction Problems","funder_award_id":"EP/F009461/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5886831683","display_name":null,"funder_award_id":"EP/F009461/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7175059544","display_name":null,"funder_award_id":"EP/F009461/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W26049824","https://openalex.org/W1497675750","https://openalex.org/W1519342765","https://openalex.org/W1567512734","https://openalex.org/W1586588101","https://openalex.org/W1934021597","https://openalex.org/W1967849786","https://openalex.org/W2020110803","https://openalex.org/W2030290736","https://openalex.org/W2036043322","https://openalex.org/W2040852548","https://openalex.org/W2045656233","https://openalex.org/W2049351696","https://openalex.org/W2065180801","https://openalex.org/W2108306139","https://openalex.org/W2110658950","https://openalex.org/W2117234597","https://openalex.org/W2119595900","https://openalex.org/W2124584833","https://openalex.org/W2126131904","https://openalex.org/W2127972252","https://openalex.org/W2131479143","https://openalex.org/W2135624048","https://openalex.org/W2139828520","https://openalex.org/W2141274633","https://openalex.org/W2142108649","https://openalex.org/W2148319469","https://openalex.org/W2148522164","https://openalex.org/W2150775571","https://openalex.org/W2151732775","https://openalex.org/W2155440340","https://openalex.org/W2155459494","https://openalex.org/W2156935079","https://openalex.org/W2157825442","https://openalex.org/W2162800060","https://openalex.org/W2162888803","https://openalex.org/W2165698076","https://openalex.org/W2913340405","https://openalex.org/W3104240813","https://openalex.org/W3121687142","https://openalex.org/W3141006818","https://openalex.org/W3148198191","https://openalex.org/W4211049957","https://openalex.org/W4232383088","https://openalex.org/W4285719527","https://openalex.org/W6629868721","https://openalex.org/W6631028693","https://openalex.org/W6640231202","https://openalex.org/W6677658955","https://openalex.org/W6677881370","https://openalex.org/W6679468046","https://openalex.org/W6680149836","https://openalex.org/W6680615919","https://openalex.org/W6680632310","https://openalex.org/W6682847631","https://openalex.org/W7062423369"],"related_works":["https://openalex.org/W2072169887","https://openalex.org/W4386272753","https://openalex.org/W2793406240","https://openalex.org/W2164129707","https://openalex.org/W4292122269","https://openalex.org/W1517763961","https://openalex.org/W2133543800","https://openalex.org/W3122927555","https://openalex.org/W1990075812","https://openalex.org/W2494929626"],"abstract_inverted_index":{"We":[0,52,82,106],"present":[1,83],"a":[2,38,78,86,110],"novel":[3],"approach":[4,114],"to":[5,35,74],"multitask":[6,23],"learning":[7,102],"in":[8,77],"classification":[9],"problems":[10],"based":[11,55,115],"on":[12,22,56,85,116],"Gaussian":[13],"process":[14],"(GP)":[15],"classification.":[16],"The":[17],"method":[18],"extends":[19],"previous":[20],"work":[21],"GP":[24],"regression,":[25],"constraining":[26],"the":[27,57,97],"overall":[28],"covariance":[29],"(across":[30],"tasks":[31],"and":[32,61,89],"data":[33],"points)":[34],"factorize":[36],"as":[37],"Kronecker":[39],"product.":[40],"Fully":[41],"Bayesian":[42],"inference":[43],"is":[44],"possible":[45],"but":[46],"time":[47],"consuming":[48],"using":[49],"sampling":[50],"techniques.":[51],"propose":[53],"approximations":[54],"popular":[58],"variational":[59],"Bayes":[60],"expectation":[62],"propagation":[63],"frameworks,":[64],"showing":[65,93],"that":[66],"they":[67],"both":[68],"achieve":[69],"excellent":[70],"accuracy":[71],"when":[72],"compared":[73],"Gibbs":[75],"sampling,":[76],"fraction":[79],"of":[80],"time.":[81],"results":[84,99],"toy":[87],"dataset":[88],"two":[90],"real":[91],"datasets,":[92],"improved":[94],"performance":[95],"against":[96],"baseline":[98],"obtained":[100],"by":[101],"each":[103],"task":[104],"independently.":[105],"also":[107],"compare":[108],"with":[109],"recently":[111],"proposed":[112],"state-of-the-art":[113],"support":[117],"vector":[118],"machines,":[119],"obtaining":[120],"comparable":[121],"or":[122],"better":[123],"results.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":9}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}