{"id":"https://openalex.org/W2099526299","doi":null,"title":"Incremental Gaussian Processes","display_name":"Incremental Gaussian Processes","publication_year":2002,"publication_date":"2002-01-01","ids":{"openalex":"https://openalex.org/W2099526299","mag":"2099526299"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.14.5306","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.5306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://isp.imm.dtu.dk/staff/jqc/./pub/nips2_03.ps.gz","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5050604937","display_name":"Joaquin Qui\u00f1onero-Candela","orcid":null,"observed_orcids":[]},"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":"Joaquin Qui\u00f1onero-Candela","raw_affiliation_strings":["Informatics & Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Informatics & Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark","institution_ids":["https://openalex.org/I96673099"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082357240","display_name":"Ole Winther","orcid":"https://orcid.org/0000-0002-1966-3205","observed_orcids":["https://orcid.org/0000-0002-1966-3205"]},"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":"Ole Winther","raw_affiliation_strings":["Informatics & Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-1966-3205","affiliations":[{"raw_affiliation_string":"Informatics & Mathematical Modelling, Technical University of Denmark, 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":1.0107,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.78109927,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":97},"biblio":{"volume":"15","issue":null,"first_page":"1025","last_page":"1032"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9951000213623047,"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":0.9951000213623047,"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/T10320","display_name":"Neural Networks and Applications","score":0.0010000000474974513,"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/T12676","display_name":"Machine Learning and ELM","score":0.00039999998989515007,"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/relevance-vector-machine","display_name":"relevance vector machine","score":0.9850000143051147},{"id":"https://openalex.org/keywords/expectation-maximization-algorithm","display_name":"expectation-maximization algorithm","score":0.8529999852180481},{"id":"https://openalex.org/keywords/incremental-training","display_name":"incremental training","score":0.8569999933242798},{"id":"https://openalex.org/keywords/sparse-bayesian-inference","display_name":"sparse Bayesian inference","score":0.5830000042915344}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6997387409210205},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6560858488082886},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.5910791158676147},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5709128975868225},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5304835438728333},{"id":"https://openalex.org/C22243797","wikidata":"https://www.wikidata.org/wiki/Q2058297","display_name":"Laplace's method","level":3,"score":0.51847904920578},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.504642128944397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4953407347202301},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.4540995657444},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4460775852203369},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4433629512786865},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44133487343788147},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.4385264217853546},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41667890548706055},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4100344777107239},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37958139181137085},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3569497764110565},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3081573247909546},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.16929519176483154},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.14.5306","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.5306","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://isp.imm.dtu.dk/staff/jqc/./pub/nips2_03.ps.gz","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.423.2264","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.423.2264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cogsys.imm.dtu.dk/staff/winther/quinonero.nips.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.826.3357","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.826.3357","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://papers.nips.cc/paper/2173-incremental-gaussian-processes.pdf","raw_type":"text"},{"id":"pmh:oai:pure.mpg.de:item_1792290","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-0013-DB41-7","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Advances in Neural Information Processing Systems 15","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:2099526299","doi":null,"is_oa":false,"landing_page_url":"http://is.tuebingen.mpg.de/fileadmin/user_upload/files/publications/NIPSD-2002-Canela.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Neural Information Processing Systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1550570395","https://openalex.org/W1567512734","https://openalex.org/W1633751774","https://openalex.org/W1648445109","https://openalex.org/W2049633694","https://openalex.org/W2051519930","https://openalex.org/W2098949458","https://openalex.org/W2112545207","https://openalex.org/W2112796928","https://openalex.org/W2123687908","https://openalex.org/W2130031702","https://openalex.org/W2137512539","https://openalex.org/W2141274633","https://openalex.org/W2145739586","https://openalex.org/W2148603752","https://openalex.org/W2149842772","https://openalex.org/W2911546748","https://openalex.org/W3119651796"],"related_works":["https://openalex.org/W7095693103","https://openalex.org/W2897787625","https://openalex.org/W1482554501","https://openalex.org/W7099286316","https://openalex.org/W1576366693","https://openalex.org/W2377204646","https://openalex.org/W2101709642","https://openalex.org/W2559331598","https://openalex.org/W7095403431","https://openalex.org/W2131620359"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,25],"consider":[4],"Tipping\u2018s":[5],"relevance":[6],"vector":[7],"machine":[8],"(RVM)":[9],"and":[10,51,84],"formalize":[11],"an":[12],"incremental":[13],"training":[14],"strategy":[15],"as":[16,89],"a":[17,31,62,76,90],"variant":[18],"of":[19,33,39,48,111],"the":[20,37,40,46,53,67,86,95,116],"expectation-maximization":[21],"(EM)":[22],"algorithm":[23],"that":[24,45,71,108],"call":[26],"subspace":[27],"EM.":[28],"Working":[29],"with":[30,102],"subset":[32],"active":[34],"basis":[35,49],"functions,":[36],"sparsity":[38],"RVM":[41],"solution":[42],"will":[43],"ensure":[44],"number":[47],"functions":[50],"thereby":[52],"computational":[54],"complexity":[55],"is":[56,72,119],"kept":[57],"low.":[58],"We":[59,93],"also":[60],"introduce":[61],"mean":[63],"field":[64],"approach":[65],"to":[66,74,80],"intractable":[68],"classification":[69],"model":[70],"expected":[73],"give":[75],"very":[77],"good":[78],"approximation":[79,88],"exact":[81],"Bayesian":[82,109],"inference":[83],"contains":[85],"Laplace":[87],"special":[91],"case.":[92],"test":[94],"algorithms":[96],"on":[97],"two":[98],"large":[99,112],"data":[100,113],"sets":[101],"O(10^3-10^4)":[103],"examples.":[104],"The":[105],"results":[106],"indicate":[107],"learning":[110],"sets,":[114],"e.g.":[115],"MNIST":[117],"database":[118],"realistic.":[120]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2016-06-24T00:00:00"}
