{"id":"https://openalex.org/W2145237058","doi":"https://doi.org/10.48550/arxiv.1206.6396","title":"Joint Optimization and Variable Selection of High-dimensional Gaussian Processes","display_name":"Joint Optimization and Variable Selection of High-dimensional Gaussian Processes","publication_year":2012,"publication_date":"2012-06-27","ids":{"openalex":"https://openalex.org/W2145237058","doi":"https://doi.org/10.48550/arxiv.1206.6396","mag":"2145237058"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1206.6396","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1206.6396","pdf_url":"https://arxiv.org/pdf/1206.6396","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1206.6396","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100427262","display_name":"Bo Chen","orcid":"https://orcid.org/0000-0001-6150-3881","observed_orcids":["https://orcid.org/0000-0001-6150-3881","https://orcid.org/0000-0001-5566-7361"]},"institutions":[{"id":"https://openalex.org/I122411786","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055","country_code":"US","type":"education","lineage":["https://openalex.org/I122411786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen, Bo","raw_affiliation_strings":["Caltech","California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Caltech","institution_ids":["https://openalex.org/I122411786"]},{"raw_affiliation_string":"California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125 USA","institution_ids":["https://openalex.org/I122411786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101555643","display_name":"Rui M. Castro","orcid":"https://orcid.org/0000-0003-4398-0718","observed_orcids":["https://orcid.org/0000-0003-4398-0718"]},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]},{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["CH","NL"],"is_corresponding":false,"raw_author_name":"Castro, Rui","raw_affiliation_strings":["Eindhoven University of Technology","ETH Zurich, Universit?atstrasse 6, 8092 Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology","institution_ids":["https://openalex.org/I83019370"]},{"raw_affiliation_string":"ETH Zurich, Universit?atstrasse 6, 8092 Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003040843","display_name":"Andreas Krause","orcid":"https://orcid.org/0000-0001-7260-9673","observed_orcids":["https://orcid.org/0000-0001-7260-9673"]},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]},{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["CH","NL"],"is_corresponding":false,"raw_author_name":"Krause, Andreas","raw_affiliation_strings":["ETH Zurich","Eindhoven University of Technology, P.O. box 513, 5600 MB Eindhoven, the Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"Eindhoven University of Technology, P.O. box 513, 5600 MB Eindhoven, the Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":61,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1379","last_page":"1386"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.00019999999494757503,"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/T10136","display_name":"Statistical Methods and Inference","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.6660000085830688},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.7110000252723694},{"id":"https://openalex.org/keywords/nonconvex-optimization","display_name":"non-convex optimization","score":0.8510000109672546},{"id":"https://openalex.org/keywords/sample-complexity","display_name":"sample complexity","score":0.9190000295639038}],"concepts":[{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.7037908434867859},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.636391282081604},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.635482668876648},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5803453326225281},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.5675394535064697},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5545383095741272},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.532392144203186},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5280070304870605},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5153509974479675},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.45844292640686035},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44293391704559326},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3640517592430115},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31318217515945435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24206006526947021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18268051743507385},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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":[],"locations_count":8,"locations":[{"id":"pmh:oai:arXiv.org:1206.6396","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1206.6396","pdf_url":"https://arxiv.org/pdf/1206.6396","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:739285","doi":null,"is_oa":false,"landing_page_url":"http://library.tue.nl/csp/dare/LinkToRepository.csp?recordnumber=739285","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:oai:library.tue.nl:739285","doi":null,"is_oa":false,"landing_page_url":"http://repository.tue.nl/739285","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:oai:pure.tue.nl:openaire_cris_publications/d72a1009-effd-42b8-8922-d3f0d25fe760","doi":null,"is_oa":false,"landing_page_url":"https://research.tue.nl/en/publications/d72a1009-effd-42b8-8922-d3f0d25fe760","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Chen, B, Castro, R M & Krause, A 2012, Joint optimization and variable selection of high-dimensional Gaussian processes. in Proceedings of the 29th International Conference on achine Learning (ICML 2012, Edinburgh, Scotland, UK, June 26-July 1, 2012). vol. 2, pp. 1423-1430, 26th International Conference on Machine Learning (ICML 2009), Montreal, Canada, 14/06/09.","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:tue:oai:library.tue.nl:739285","doi":null,"is_oa":false,"landing_page_url":"http://repository.tue.nl/739285","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/other"},{"id":"pmh:tue:oai:pure.tue.nl:publications/d72a1009-effd-42b8-8922-d3f0d25fe760","doi":null,"is_oa":false,"landing_page_url":"https://research.tue.nl/nl/publications/d72a1009-effd-42b8-8922-d3f0d25fe760","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 29th International Conference on achine Learning (ICML 2012, Edinburgh, Scotland, UK, June 26-July 1, 2012), 2, 1423 - 1430","raw_type":"info:eu-repo/semantics/conferencepaper"},{"id":"doi:10.48550/arxiv.1206.6396","doi":"https://doi.org/10.48550/arxiv.1206.6396","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1206.6396","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"mag:2145237058","doi":null,"is_oa":false,"landing_page_url":"http://icml.cc/2012/papers/714.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"International Conference on Machine Learning","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1206.6396","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1206.6396","pdf_url":"https://arxiv.org/pdf/1206.6396","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3911128648","display_name":"Gaussian Process Bandit Optimization: Theory and Applications","funder_award_id":"137971","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"},{"id":"https://openalex.org/G6345279525","display_name":"CAREER: Coping with the Data Deluge - Algorithms, Human Aspects and Applications","funder_award_id":"0953413","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G993971353","display_name":null,"funder_award_id":"200021","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2145237058.pdf","grobid_xml":"https://content.openalex.org/works/W2145237058.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1483202606","https://openalex.org/W1746819321","https://openalex.org/W1968261502","https://openalex.org/W2021774297","https://openalex.org/W2023293102","https://openalex.org/W2050834445","https://openalex.org/W2091082553","https://openalex.org/W2099201756","https://openalex.org/W2111992537","https://openalex.org/W2135046866","https://openalex.org/W2156540265","https://openalex.org/W2206616202","https://openalex.org/W2213359196","https://openalex.org/W2911546748","https://openalex.org/W2951665052","https://openalex.org/W7097425697"],"related_works":["https://openalex.org/W3213239135","https://openalex.org/W2544432336","https://openalex.org/W2897704690","https://openalex.org/W2317976735","https://openalex.org/W4225602300","https://openalex.org/W4225669927","https://openalex.org/W3081237658","https://openalex.org/W3094797812","https://openalex.org/W6948271132","https://openalex.org/W2968630476"],"abstract_inverted_index":{"Maximizing":[0],"high-dimensional,":[1],"non-convex":[2],"functions":[3],"through":[4],"noisy":[5],"observations":[6],"is":[7,56],"a":[8,32,35],"notoriously":[9],"hard":[10],"problem,":[11],"but":[12],"one":[13],"that":[14,42,54],"arises":[15],"in":[16],"many":[17],"applications.":[18],"In":[19],"this":[20,24],"paper,":[21],"we":[22,52],"tackle":[23],"challenge":[25],"by":[26],"modeling":[27],"the":[28,43,75,95],"unknown":[29,44],"function":[30,45],"as":[31,82,84],"sample":[33,76],"from":[34],"high-dimensional":[36],"Gaussian":[37],"process":[38],"(GP)":[39],"distribution.":[40],"Assuming":[41],"only":[46],"depends":[47],"on":[48,94,100],"few":[49],"relevant":[50],"variables,":[51],"show":[53],"it":[55],"possible":[57],"to":[58],"perform":[59],"joint":[60],"variable":[61,79],"selection":[62],"and":[63,81],"GP":[64],"optimization.":[65],"We":[66,89],"provide":[67,91],"strong":[68],"performance":[69],"guarantees":[70],"for":[71],"our":[72,98],"algorithm,":[73],"bounding":[74],"complexity":[77],"of":[78,97],"selection,":[80],"well":[83],"providing":[85],"cumulative":[86],"regret":[87],"bounds.":[88],"further":[90],"empirical":[92],"evidence":[93],"effectiveness":[96],"algorithm":[99],"several":[101],"benchmark":[102],"optimization":[103],"problems.":[104]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":6}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-06-24T00:00:00"}
