{"id":"https://openalex.org/W3084079134","doi":"https://doi.org/10.48550/arxiv.2009.03586","title":"Hyperparameter Optimization via Sequential Uniform Designs","display_name":"Hyperparameter Optimization via Sequential Uniform Designs","publication_year":2020,"publication_date":"2020-09-08","ids":{"openalex":"https://openalex.org/W3084079134","doi":"https://doi.org/10.48550/arxiv.2009.03586","mag":"3084079134"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2009.03586","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.03586","pdf_url":"https://arxiv.org/pdf/2009.03586","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/2009.03586","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002987540","display_name":"Zebin Yang","orcid":"https://orcid.org/0000-0002-3271-883X","observed_orcids":["https://orcid.org/0000-0002-3271-883X"]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yang, Zebin","raw_affiliation_strings":["Department of Statistics and Actuarial Science University of Hong Kong Pokfulam Road , Hong Kong","UNIVERSITY OF HONG KONG"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Actuarial Science University of Hong Kong Pokfulam Road , Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"UNIVERSITY OF HONG KONG","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101664060","display_name":"Aijun Zhang","orcid":"https://orcid.org/0000-0001-9729-9018","observed_orcids":["https://orcid.org/0000-0001-9729-9018"]},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK","US"],"is_corresponding":false,"raw_author_name":"Zhang, Aijun","raw_affiliation_strings":["Department of Statistics and Actuarial Science University of Hong Kong Pokfulam Road , Hong Kong","\u2020University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Actuarial Science University of Hong Kong Pokfulam Road , Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"\u2020University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"149","first_page":"1","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.5698000192642212,"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/T11798","display_name":"Optimal Experimental Design Methods","score":0.5698000192642212,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.3544999957084656,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.00930000003427267,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"hyperparameter optimization","score":1.0},{"id":"https://openalex.org/keywords/computer-experiments","display_name":"computer experiments","score":0.7390000224113464},{"id":"https://openalex.org/keywords/automated-machine-learning","display_name":"automated machine learning","score":0.8740000128746033},{"id":"https://openalex.org/keywords/global-optimization","display_name":"global optimization","score":0.7590000033378601},{"id":"https://openalex.org/keywords/adaptive-design","display_name":"adaptive design","score":0.4659999907016754},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"parallel computing","score":0.39500001072883606}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8285762071609497},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48559755086898804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29974257946014404}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2009.03586","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.03586","pdf_url":"https://arxiv.org/pdf/2009.03586","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":"doi:10.48550/arxiv.2009.03586","doi":"https://doi.org/10.48550/arxiv.2009.03586","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2009.03586","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:3192495203","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2009.03586","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":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2009.03586","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.03586","pdf_url":"https://arxiv.org/pdf/2009.03586","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":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3084079134.pdf","grobid_xml":"https://content.openalex.org/works/W3084079134.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W76331760","https://openalex.org/W100047375","https://openalex.org/W1437335841","https://openalex.org/W1510052597","https://openalex.org/W1588486985","https://openalex.org/W1680603978","https://openalex.org/W1758903565","https://openalex.org/W1871676304","https://openalex.org/W1887758993","https://openalex.org/W1971670438","https://openalex.org/W1981270896","https://openalex.org/W2003657827","https://openalex.org/W2040396531","https://openalex.org/W2043419861","https://openalex.org/W2070425636","https://openalex.org/W2090133507","https://openalex.org/W2092984401","https://openalex.org/W2096994080","https://openalex.org/W2097998348","https://openalex.org/W2106614481","https://openalex.org/W2112364454","https://openalex.org/W2113145584","https://openalex.org/W2131241448","https://openalex.org/W2151582349","https://openalex.org/W2153635508","https://openalex.org/W2173248099","https://openalex.org/W2182361439","https://openalex.org/W2192203593","https://openalex.org/W2266822037","https://openalex.org/W2553303224","https://openalex.org/W2607442583","https://openalex.org/W2608595939","https://openalex.org/W2792338380","https://openalex.org/W2802235618","https://openalex.org/W2895503911","https://openalex.org/W2908974255","https://openalex.org/W2909800602","https://openalex.org/W2913566062","https://openalex.org/W2963659022","https://openalex.org/W2963815651","https://openalex.org/W2964284859"],"related_works":["https://openalex.org/W3024879108","https://openalex.org/W3214985046","https://openalex.org/W4305007508","https://openalex.org/W3197052919","https://openalex.org/W4399677660","https://openalex.org/W4416921201","https://openalex.org/W4287078451","https://openalex.org/W7125909220","https://openalex.org/W2400219576","https://openalex.org/W4211116959"],"abstract_inverted_index":{"Hyperparameter":[0],"optimization":[1,31,111],"(HPO)":[2],"plays":[3],"a":[4,15,29,38,43,87,134],"central":[5],"role":[6],"in":[7],"the":[8,19,54,66,75,96,121],"automated":[9],"machine":[10],"learning":[11],"(AutoML).":[12],"It":[13],"is":[14,57,93],"challenging":[16],"task":[17],"as":[18,37],"response":[20],"surfaces":[21],"of":[22,68,100],"hyperparameters":[23],"are":[24,79,106],"generally":[25],"unknown,":[26],"hence":[27],"essentially":[28],"global":[30,110],"problem.":[32],"This":[33],"paper":[34],"reformulates":[35],"HPO":[36,114,127],"computer":[39],"experiment":[40],"and":[41,71,113,129,136],"proposes":[42],"novel":[44],"sequential":[45],"uniform":[46,90],"design":[47,63,77,91,102],"(SeqUD)":[48],"strategy":[49,124],"with":[50,60,82],"three-fold":[51],"advantages:":[52],"a)":[53],"hyperparameter":[55],"space":[56],"adaptively":[58],"explored":[59],"evenly":[61],"spread":[62],"points,":[64],"without":[65],"need":[67],"expensive":[69],"meta-modeling":[70],"acquisition":[72],"optimization;":[73],"b)":[74],"batch-by-batch":[76],"points":[78],"sequentially":[80],"generated":[81],"parallel":[83],"processing":[84],"support;":[85],"c)":[86],"new":[88],"augmented":[89],"algorithm":[92],"developed":[94],"for":[95],"efficient":[97],"real-time":[98],"generation":[99],"follow-up":[101],"points.":[103],"Extensive":[104],"experiments":[105],"conducted":[107],"on":[108],"both":[109],"tasks":[112],"applications.":[115],"The":[116],"numerical":[117],"results":[118],"show":[119],"that":[120],"proposed":[122],"SeqUD":[123],"outperforms":[125],"benchmark":[126],"methods,":[128],"it":[130],"can":[131],"be":[132],"therefore":[133],"promising":[135],"competitive":[137],"alternative":[138],"to":[139],"existing":[140],"AutoML":[141],"tools.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2020-09-14T00:00:00"}