{"id":"https://openalex.org/W2913573237","doi":"https://doi.org/10.1109/ivcnz.2018.8634788","title":"Sample-Efficient Optimization Using Bayesian Neural Networks","display_name":"Sample-Efficient Optimization Using Bayesian Neural Networks","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2913573237","doi":"https://doi.org/10.1109/ivcnz.2018.8634788","mag":"2913573237"},"language":"en","primary_location":{"id":"doi:10.1109/ivcnz.2018.8634788","doi":"https://doi.org/10.1109/ivcnz.2018.8634788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz.2018.8634788","pdf_url":null,"source":{"id":"https://openalex.org/S7407088831","display_name":"International Conference on Image and Vision Computing New Zealand (IVCNZ)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Image and Vision Computing New Zealand (IVCNZ)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5024516982","display_name":"Mashall Aryan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Mashall Aryan","raw_affiliation_strings":["Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020402037","display_name":"Marcus R. Frean","orcid":"https://orcid.org/0000-0001-5840-8760","observed_orcids":["https://orcid.org/0000-0001-5840-8760"]},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Marcus Frean","raw_affiliation_strings":["Victoria University of Wellington, Wellington, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington, Wellington, New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057936203","display_name":"John P. Lewis","orcid":"https://orcid.org/0000-0002-6835-7263","observed_orcids":["https://orcid.org/0000-0002-6835-7263"]},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"John Lewis","raw_affiliation_strings":["Victoria University of Wellington & SEED Electronic Arts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington & SEED Electronic Arts, USA","institution_ids":["https://openalex.org/I41156924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41156924"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.7821999788284302,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.7821999788284302,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.15520000457763672,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.011300000362098217,"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/bayesian-neural-networks","display_name":"Bayesian neural networks","score":0.9959999918937683},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.6869999766349792},{"id":"https://openalex.org/keywords/expensive-function-evaluations","display_name":"expensive function evaluations","score":0.6470000147819519},{"id":"https://openalex.org/keywords/gaussian-processes","display_name":"Gaussian processes","score":0.6209999918937683},{"id":"https://openalex.org/keywords/surrogate-modeling","display_name":"surrogate models","score":0.5929999947547913}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7234987616539001},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6939179301261902},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6109858155250549},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6047901511192322},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5980875492095947},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5334829092025757},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5306887626647949},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5149184465408325},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47651422023773193},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.44993355870246887},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4480760097503662},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4420662522315979},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43670815229415894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2118425965309143},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20140951871871948},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivcnz.2018.8634788","doi":"https://doi.org/10.1109/ivcnz.2018.8634788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz.2018.8634788","pdf_url":null,"source":{"id":"https://openalex.org/S7407088831","display_name":"International Conference on Image and Vision Computing New Zealand (IVCNZ)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Image and Vision Computing New Zealand (IVCNZ)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W582134693","https://openalex.org/W1502922572","https://openalex.org/W1510052597","https://openalex.org/W1567512734","https://openalex.org/W1590183771","https://openalex.org/W1591505807","https://openalex.org/W1595797227","https://openalex.org/W1702387805","https://openalex.org/W1746819321","https://openalex.org/W1798702550","https://openalex.org/W1888596299","https://openalex.org/W1959608418","https://openalex.org/W1976355201","https://openalex.org/W2018705428","https://openalex.org/W2099201756","https://openalex.org/W2106411961","https://openalex.org/W2131241448","https://openalex.org/W2134603844","https://openalex.org/W2139701068","https://openalex.org/W2143574249","https://openalex.org/W2151238122","https://openalex.org/W2155910151","https://openalex.org/W2317747985","https://openalex.org/W2478027467","https://openalex.org/W2478899349","https://openalex.org/W2493480577","https://openalex.org/W2522830361","https://openalex.org/W2556372419","https://openalex.org/W2577537660","https://openalex.org/W2592733333","https://openalex.org/W2603221039","https://openalex.org/W2765332150","https://openalex.org/W2787825417","https://openalex.org/W2884298516","https://openalex.org/W2950220847","https://openalex.org/W2963001956","https://openalex.org/W2963717915","https://openalex.org/W2963977107","https://openalex.org/W3105047877","https://openalex.org/W3121200744","https://openalex.org/W4211049957","https://openalex.org/W4236876623","https://openalex.org/W4243223086","https://openalex.org/W6683090604","https://openalex.org/W6786151234"],"related_works":["https://openalex.org/W4205091727","https://openalex.org/W3213195002","https://openalex.org/W7098805449","https://openalex.org/W4287202213","https://openalex.org/W4379089641","https://openalex.org/W7135397024","https://openalex.org/W4294790506","https://openalex.org/W2556372419","https://openalex.org/W3159660816","https://openalex.org/W2161767008"],"abstract_inverted_index":{"Multiple":[0],"problems":[1],"in":[2,13,118],"robotics,":[3],"vision,":[4],"and":[5,28,77,152],"graphics":[6],"can":[7,18],"be":[8,19,86],"considered":[9],"as":[10,88],"optimization":[11,166],"problems,":[12,41],"which":[14,94],"the":[15,29,83,97,113,124],"loss":[16],"surface":[17],"evaluated":[20],"only":[21],"at":[22],"a":[23,67,104,107,161],"collection":[24],"of":[25,51,99,132,164],"sample":[26],"locations":[27],"problem":[30],"is":[31,92,123],"regularized":[32],"with":[33],"an":[34],"implicit":[35],"or":[36,147,158],"explicit":[37],"prior.":[38],"In":[39],"some":[40],"however,":[42],"samples":[43],"are":[44,145,156],"expensive":[45],"to":[46,59,63,106,149],"obtain.":[47],"This":[48],"motivates":[49],"consideration":[50],"sample-efficient":[52],"optimization.":[53],"A":[54],"successful":[55],"approach":[56],"has":[57,95],"been":[58],"choose":[60],"new":[61,90],"points":[62,76],"evaluate":[64],"by":[65],"considering":[66],"distribution":[68,84,117],"over":[69,109],"plausible":[70],"surfaces":[71],"conditioned":[72],"on":[73,160],"all":[74],"previous":[75],"their":[78],"evaluations.":[79],"To":[80],"do":[81],"this":[82,121],"must":[85],"updated":[87],"each":[89],"evaluation":[91],"acquired,":[93],"motivated":[96],"development":[98],"Bayesian":[100,135],"methods":[101],"that":[102,140,144,154],"update":[103],"prior":[105,116],"posterior":[108],"functions.":[110],"By":[111],"far,":[112],"most":[114],"common":[115],"use":[119],"for":[120],"application":[122],"Gaussian":[125,150],"process.":[126],"Here,":[127],"we":[128],"consider":[129],"another":[130],"family":[131],"priors,":[133],"namely":[134],"Neural":[136],"Networks.":[137],"We":[138],"argue":[139],"these":[141],"exhibit":[142],"strengths":[143],"different":[146],"complementary":[148],"processes":[151],"show":[153],"they":[155],"competitive":[157],"superior":[159],"wide":[162],"range":[163],"test":[165],"problems.":[167]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-02-21T00:00:00"}