{"id":"https://openalex.org/W3035803417","doi":"https://doi.org/10.23919/date48585.2020.9116366","title":"An Efficient Bayesian Optimization Approach for Analog Circuit Synthesis via Sparse Gaussian Process Modeling","display_name":"An Efficient Bayesian Optimization Approach for Analog Circuit Synthesis via Sparse Gaussian Process Modeling","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3035803417","doi":"https://doi.org/10.23919/date48585.2020.9116366","mag":"3035803417"},"language":"en","primary_location":{"id":"doi:10.23919/date48585.2020.9116366","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date48585.2020.9116366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5054587707","display_name":"Biao He","orcid":"https://orcid.org/0000-0003-0343-1087"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao He","raw_affiliation_strings":["State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I24943067","https://openalex.org/I4210132426"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017568991","display_name":"Shuhan Zhang","orcid":"https://orcid.org/0000-0002-3959-8893"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhan Zhang","raw_affiliation_strings":["State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I24943067","https://openalex.org/I4210132426"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045464812","display_name":"Fan Yang","orcid":"https://orcid.org/0000-0003-2164-8175"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yang","raw_affiliation_strings":["State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I24943067","https://openalex.org/I4210132426"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037328458","display_name":"Changhao Yan","orcid":"https://orcid.org/0000-0002-8936-3945"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changhao Yan","raw_affiliation_strings":["State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I24943067","https://openalex.org/I4210132426"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054960059","display_name":"Dian Zhou","orcid":"https://orcid.org/0000-0002-2648-5232"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dian Zhou","raw_affiliation_strings":["Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, U.S.A","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064213921","display_name":"Xuan Zeng","orcid":"https://orcid.org/0000-0002-8097-4053"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]},{"id":"https://openalex.org/I4210132426","display_name":"Shanghai Fudan Microelectronics (China)","ror":"https://ror.org/02vfj3j86","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132426"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Zeng","raw_affiliation_strings":["State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of ASIC & System, School of Microelectronics, Fudan University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I24943067","https://openalex.org/I4210132426"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.0676,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.97834941,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"67","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9957000017166138,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.7913062572479248},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.7809393405914307},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.6059816479682922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5544278025627136},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5435447692871094},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5116334557533264},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5057632923126221},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5049906373023987},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.4558826684951782},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4446121156215668},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42162439227104187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41328126192092896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2937844395637512},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.13860741257667542}],"concepts":[{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.7913062572479248},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.7809393405914307},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.6059816479682922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5544278025627136},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5435447692871094},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5116334557533264},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5057632923126221},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5049906373023987},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4558826684951782},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4446121156215668},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42162439227104187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41328126192092896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2937844395637512},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.13860741257667542},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date48585.2020.9116366","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date48585.2020.9116366","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1964239621","https://openalex.org/W2051434435","https://openalex.org/W2065183815","https://openalex.org/W2068923837","https://openalex.org/W2074046446","https://openalex.org/W2092297295","https://openalex.org/W2099768828","https://openalex.org/W2121200747","https://openalex.org/W2137956165","https://openalex.org/W2144133630","https://openalex.org/W2144873182","https://openalex.org/W2154237706","https://openalex.org/W2155811837","https://openalex.org/W2171048418","https://openalex.org/W2185967851","https://openalex.org/W2192203593","https://openalex.org/W2386578045","https://openalex.org/W2769791151","https://openalex.org/W2945689147","https://openalex.org/W2989851762","https://openalex.org/W3100083105","https://openalex.org/W6674989108","https://openalex.org/W6680058137","https://openalex.org/W6683185311"],"related_works":["https://openalex.org/W3104422856","https://openalex.org/W4206864338","https://openalex.org/W4287867179","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W3134690064","https://openalex.org/W2056958800","https://openalex.org/W4210726438"],"abstract_inverted_index":{"Bayesian":[0,67,125],"optimization":[1,68,126],"with":[2],"Gaussian":[3,33,53,90,116,131,149,157],"Process":[4,132],"(GP)":[5],"models":[6,35,92],"has":[7,73],"been":[8,74],"proposed":[9,75,198],"for":[10,17,28],"analog":[11],"synthesis":[12],"since":[13],"it":[14,172],"is":[15,43,62,136],"efficient":[16],"the":[18,25,44,52,82,100,112,154,161,165,169,175,194,197],"optimizations":[19],"of":[20,32,46,51,85,89,115,168,178,196],"expensive":[21],"black-box":[22],"functions.":[23],"However,":[24,98],"computational":[26,83,176],"cost":[27,84,177],"training":[29,86,180],"and":[30,38,87,95,181,185],"prediction":[31,88,182],"process":[34,54,91,150,158],"are":[36],"O(N3)":[37],"O(N2),":[39],"respectively,":[40],"where":[41],"N":[42,61,141],"number":[45],"data":[47],"points.":[48],"The":[49,134],"overhead":[50],"modeling":[55,166],"would":[56,110],"not":[57],"be":[58],"negligible":[59],"as":[60],"relatively":[63],"large.":[64],"Recently,":[65],"a":[66,123,147],"approach":[69,127],"using":[70,106,128],"neural":[71,107],"network":[72,108],"to":[76,93,103,137,145,152,163,183,192],"address":[77],"this":[78,119],"problem.":[79],"It":[80],"reduces":[81,174],"O(N)":[94,184],"O(1),":[96,186],"respectively.":[97,187],"reducing":[99],"infinite-dimensional":[101],"kernel":[102,105],"finite-dimensional":[104],"mapping":[109],"weaken":[111],"characterization":[113],"ability":[114,167],"process.":[117],"In":[118],"paper,":[120],"we":[121],"propose":[122],"novel":[124],"Sparse":[129],"Pseudo-input":[130],"(SPGP).":[133],"idea":[135],"use":[138],"M":[139],"<;":[140],"so-called":[142],"inducing":[143],"points":[144],"build":[146],"sparse":[148],"model":[151],"approximate":[153],"conventional":[155],"exact":[156],"model.":[159],"Without":[160],"need":[162],"sacrifice":[164],"surrogate":[170],"model,":[171],"also":[173],"both":[179],"Several":[188],"experiments":[189],"were":[190],"provided":[191],"demonstrate":[193],"efficiency":[195],"approach.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}