{"id":"https://openalex.org/W4280634883","doi":"https://doi.org/10.1007/s10994-022-06170-3","title":"JGPR: a computationally efficient multi-target Gaussian process regression algorithm","display_name":"JGPR: a computationally efficient multi-target Gaussian process regression algorithm","publication_year":2022,"publication_date":"2022-05-11","ids":{"openalex":"https://openalex.org/W4280634883","doi":"https://doi.org/10.1007/s10994-022-06170-3"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-022-06170-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06170-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06170-3.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06170-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058105340","display_name":"Mohammad Nabati","orcid":"https://orcid.org/0000-0002-4847-9829"},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Mohammad Nabati","raw_affiliation_strings":["Cognitive Telecommunication Research Group, Department of Telecommunications, Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, 19839-69411, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Telecommunication Research Group, Department of Telecommunications, Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, 19839-69411, Iran","institution_ids":["https://openalex.org/I48379061"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065961805","display_name":"Seyed Ali Ghorashi","orcid":"https://orcid.org/0000-0002-2910-9208"},"institutions":[{"id":"https://openalex.org/I157227730","display_name":"University of East London","ror":"https://ror.org/057jrqr44","country_code":"GB","type":"education","lineage":["https://openalex.org/I157227730"]},{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["GB","IR"],"is_corresponding":false,"raw_author_name":"Seyed Ali Ghorashi","raw_affiliation_strings":["Cognitive Telecommunication Research Group, Department of Telecommunications, Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, 19839-69411, Iran","School of Architecture, Computing and Engineering, University of East London, London, E16 2RD, UK"],"raw_orcid":"https://orcid.org/0000-0002-2910-9208","affiliations":[{"raw_affiliation_string":"Cognitive Telecommunication Research Group, Department of Telecommunications, Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, 19839-69411, Iran","institution_ids":["https://openalex.org/I48379061"]},{"raw_affiliation_string":"School of Architecture, Computing and Engineering, University of East London, London, E16 2RD, UK","institution_ids":["https://openalex.org/I157227730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046458978","display_name":"Reza Shahbazian","orcid":"https://orcid.org/0000-0002-2313-6002"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reza Shahbazian","raw_affiliation_strings":["Department of Electrical Engineering, Faculty of Technology and Engineering, Standard Research Institute, Alborz, 31745-139, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Technology and Engineering, Standard Research Institute, Alborz, 31745-139, Iran","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5058105340"],"corresponding_institution_ids":["https://openalex.org/I48379061"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":null,"fwci":2.4971,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.90573654,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"111","issue":"6","first_page":"1987","last_page":"2010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9973999857902527,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9973999857902527,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9968000054359436,"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":0.9961000084877014,"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/overfitting","display_name":"Overfitting","score":0.7606143355369568},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6935882568359375},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.6659967303276062},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6094880700111389},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5867069363594055},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5632221698760986},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5452644228935242},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.509238600730896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48241695761680603},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.47141027450561523},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4693278670310974},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.43813666701316833},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33007991313934326},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.29266026616096497},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17735359072685242},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1439894735813141},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09656259417533875}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7606143355369568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6935882568359375},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.6659967303276062},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6094880700111389},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5867069363594055},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5632221698760986},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5452644228935242},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.509238600730896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48241695761680603},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.47141027450561523},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4693278670310974},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.43813666701316833},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33007991313934326},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.29266026616096497},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17735359072685242},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1439894735813141},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09656259417533875},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s10994-022-06170-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06170-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06170-3.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:repository.uel.ac.uk:8q995","is_oa":false,"landing_page_url":"https://repository.uel.ac.uk/item/8q995","pdf_url":null,"source":{"id":"https://openalex.org/S4306401301","display_name":"UEL Research Repository (University of East London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I157227730","host_organization_name":"University of East London","host_organization_lineage":["https://openalex.org/I157227730"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"journal-article"},{"id":"pmh:oai:iris.unipa.it:10447/696247","is_oa":true,"landing_page_url":"https://hdl.handle.net/10447/696247","pdf_url":null,"source":{"id":"https://openalex.org/S4306401065","display_name":"Nova Science Publishers (Nova Science Publishers, Inc.)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s10994-022-06170-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06170-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06170-3.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4280634883.pdf","grobid_xml":"https://content.openalex.org/works/W4280634883.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1487760768","https://openalex.org/W1493968464","https://openalex.org/W1501503542","https://openalex.org/W1550629956","https://openalex.org/W1565746575","https://openalex.org/W1571076699","https://openalex.org/W1574447377","https://openalex.org/W1585754671","https://openalex.org/W1903038885","https://openalex.org/W1914247575","https://openalex.org/W1968772851","https://openalex.org/W1969885422","https://openalex.org/W2078339956","https://openalex.org/W2095705004","https://openalex.org/W2097334502","https://openalex.org/W2135046866","https://openalex.org/W2154095747","https://openalex.org/W2160166502","https://openalex.org/W2167503371","https://openalex.org/W2283039974","https://openalex.org/W2597701578","https://openalex.org/W2718193527","https://openalex.org/W2787894218","https://openalex.org/W2791482549","https://openalex.org/W2879687780","https://openalex.org/W2963754333","https://openalex.org/W2971238384","https://openalex.org/W3008773008","https://openalex.org/W3104621635","https://openalex.org/W3118067057","https://openalex.org/W3125261624","https://openalex.org/W4211049957","https://openalex.org/W4301014524","https://openalex.org/W4388284198","https://openalex.org/W6600195515","https://openalex.org/W6677658955","https://openalex.org/W6690827749","https://openalex.org/W6742058293","https://openalex.org/W6842097421"],"related_works":["https://openalex.org/W4298369531","https://openalex.org/W3155135229","https://openalex.org/W2141609920","https://openalex.org/W2912851808","https://openalex.org/W4294619368","https://openalex.org/W4380558509","https://openalex.org/W4286748465","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W3118984993"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
