{"id":"https://openalex.org/W4410823069","doi":"https://doi.org/10.1609/aaaiss.v5i1.35585","title":"DyESP: Accelerating Hyperparameter-Architecture Search via Dynamic Exploration and Space Pruning","display_name":"DyESP: Accelerating Hyperparameter-Architecture Search via Dynamic Exploration and Space Pruning","publication_year":2025,"publication_date":"2025-05-28","ids":{"openalex":"https://openalex.org/W4410823069","doi":"https://doi.org/10.1609/aaaiss.v5i1.35585"},"language":"en","primary_location":{"id":"doi:10.1609/aaaiss.v5i1.35585","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaaiss.v5i1.35585","pdf_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/35585/37740","source":{"id":"https://openalex.org/S4389157828","display_name":"Proceedings of the AAAI Symposium Series","issn_l":"2994-4317","issn":["2994-4317"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Symposium Series","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/35585/37740","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038109764","display_name":"Xukun Liu","orcid":"https://orcid.org/0000-0002-4608-9448"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xukun Liu","raw_affiliation_strings":["Northwestern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019085046","display_name":"Haoze Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoze Lv","raw_affiliation_strings":["Southern University of Science and Technology (SUSTech)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology (SUSTech)","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001030192","display_name":"Fenglong Ma","orcid":"https://orcid.org/0000-0002-4999-0303"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fenglong Ma","raw_affiliation_strings":["The Pennsylvania State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100342203","display_name":"Chi Wang","orcid":"https://orcid.org/0000-0001-6991-9398"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I4210090411","display_name":"Google DeepMind (United Kingdom)","ror":"https://ror.org/00971b260","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210090411","https://openalex.org/I4210128969"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Chi Wang","raw_affiliation_strings":["Google DeepMind"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google DeepMind","institution_ids":["https://openalex.org/I1291425158","https://openalex.org/I4210090411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068433690","display_name":"Dongkuan Xu","orcid":"https://orcid.org/0000-0002-1456-9658"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongkuan (DK) Xu","raw_affiliation_strings":["North Carolina State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina State University","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"1","first_page":"172","last_page":"179"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9603999853134155,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10260","display_name":"Software Engineering Research","score":0.9603999853134155,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9559999704360962,"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":0.953499972820282,"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/pruning","display_name":"Pruning","score":0.8946982622146606},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.8818373680114746},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.6242355704307556},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5782032608985901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5416309237480164},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43481892347335815},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4215025305747986},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3314565420150757},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.10618075728416443},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07458773255348206}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8946982622146606},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8818373680114746},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.6242355704307556},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5782032608985901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5416309237480164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43481892347335815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4215025305747986},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3314565420150757},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10618075728416443},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07458773255348206},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaaiss.v5i1.35585","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaaiss.v5i1.35585","pdf_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/35585/37740","source":{"id":"https://openalex.org/S4389157828","display_name":"Proceedings of the AAAI Symposium Series","issn_l":"2994-4317","issn":["2994-4317"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Symposium Series","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaaiss.v5i1.35585","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaaiss.v5i1.35585","pdf_url":"https://ojs.aaai.org/index.php/AAAI-SS/article/download/35585/37740","source":{"id":"https://openalex.org/S4389157828","display_name":"Proceedings of the AAAI Symposium Series","issn_l":"2994-4317","issn":["2994-4317"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Symposium Series","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3348058117","display_name":"Harnessing links between historical business and household microdata and street-view images to assess transit-induced neighborhood changes at small spatial scales","funder_award_id":"2416846","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8809419540","display_name":"Collaborative Research: CyberTraining: Implementation: Medium: EcoTern: Pioneering a CI Workforce for Sustainable and Transdisciplinary Environmental Science Research","funder_award_id":"2417850","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410823069.pdf","grobid_xml":"https://content.openalex.org/works/W4410823069.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4390421286","https://openalex.org/W2602382373","https://openalex.org/W3003615511","https://openalex.org/W4285827128","https://openalex.org/W3198113463","https://openalex.org/W2787698406","https://openalex.org/W2963844355","https://openalex.org/W4361251046","https://openalex.org/W98577079","https://openalex.org/W590712855"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"introduce":[4],"DyESP,":[5],"a":[6,41,52,88,92],"novel":[7],"approach":[8],"that":[9,43,183],"unites":[10],"dynamic":[11],"exploration":[12,146,176],"with":[13,164],"space":[14,59],"pruning":[15],"to":[16,35,55,69,97,143,174],"expedite":[17],"the":[18,26,45,57,72,76,85,109,118,129,134,139,145,150,159,175],"combined":[19],"search":[20,32,46,73,110],"of":[21,30,190],"hyperparameters":[22],"and":[23,28,51,99,111,122,148,171,193],"architecture,":[24],"enhancing":[25],"efficiency":[27],"accuracy":[29],"hyperparameter-architecture":[31],"(HAS).":[33],"Central":[34],"DyESP":[36,184],"are":[37,126],"two":[38],"innovative":[39],"components:":[40],"meta-scheduler":[42,65,160],"customizes":[44],"strategy":[47,152],"for":[48,153,168],"varying":[49],"spaces":[50],"pruner":[53,86],"designed":[54],"minimize":[56],"hyperparameter":[58],"by":[60,138],"discarding":[61],"suboptimal":[62],"configurations.":[63],"The":[64,115],"leverages":[66],"historical":[67,135],"data":[68],"dynamically":[70],"refine":[71,149],"direction,":[74],"targeting":[75],"most":[77],"promising":[78],"areas":[79],"while":[80],"minimizing":[81],"unnecessary":[82],"exploration.":[83],"Meanwhile,":[84],"employs":[87],"surrogate":[89],"model,":[90],"specifically":[91],"fine-tuned":[93],"multilayer":[94],"perceptron":[95],"(MLP),":[96],"predict":[98],"eliminate":[100],"inferior":[101],"configurations":[102],"based":[103],"on":[104,179,195],"static":[105],"metrics,":[106],"thereby":[107],"streamlining":[108],"conserving":[112],"computational":[113],"resources.":[114],"results":[116],"from":[117],"pruner,":[119],"which":[120],"identifies":[121],"removes":[123],"underperforming":[124],"configurations,":[125],"fed":[127],"into":[128],"meta-scheduler.":[130],"This":[131,156],"process":[132],"updates":[133],"dataset":[136],"used":[137],"meta-scheduler,":[140],"enabling":[141],"it":[142],"adjust":[144],"degree":[147],"sampling":[151],"subsequent":[154],"iterations.":[155],"integration":[157],"ensures":[158],"is":[161],"continually":[162],"updated":[163],"relevant":[165],"data,":[166],"allowing":[167],"more":[169],"accurate":[170],"timely":[172],"adjustments":[173],"strategy.":[177],"Experiments":[178],"various":[180],"benchmarks":[181],"show":[182],"outperforms":[185],"existing":[186],"methods":[187],"in":[188],"terms":[189],"both":[191],"speed":[192],"stability":[194],"almost":[196],"all":[197],"benchmarks.":[198]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}