{"id":"https://openalex.org/W7054288083","doi":null,"title":"Adaptive Hyperparameter Selection for Differentially Private Gradient Descent","display_name":"Adaptive Hyperparameter Selection for Differentially Private Gradient Descent","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W7054288083"},"language":"en","primary_location":{"id":"pmh:oai:DiVA.org:uu-516854","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-516854","pdf_url":"https://uu.diva-portal.org/smash/get/diva2:1815963/FULLTEXT01","source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I86987016","host_organization_name":"KTH Royal Institute of Technology","host_organization_lineage":["https://openalex.org/I86987016"],"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"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://uu.diva-portal.org/smash/get/diva2:1815963/FULLTEXT01","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067232508","display_name":"Dominik Fay","orcid":"https://orcid.org/0000-0002-5530-2714","observed_orcids":["https://orcid.org/0000-0002-5530-2714"]},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fay, Dominik","raw_affiliation_strings":["Division of Decision and Control Systems KTH Royal Institute of Technology Elekta"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Decision and Control Systems KTH Royal Institute of Technology Elekta","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054704457","display_name":"Sindri Magn\u00fasson","orcid":"https://orcid.org/0000-0002-6617-8683","observed_orcids":["https://orcid.org/0000-0002-6617-8683"]},"institutions":[{"id":"https://openalex.org/I161593684","display_name":"Stockholm University","ror":"https://ror.org/05f0yaq80","country_code":"SE","type":"education","lineage":["https://openalex.org/I161593684"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Magn\u00fasson, Sindri","raw_affiliation_strings":["Department of Computer and Systems Sciences Stockholm University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Systems Sciences Stockholm University","institution_ids":["https://openalex.org/I161593684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032491456","display_name":"Jens Sj\u00f6lund","orcid":"https://orcid.org/0000-0002-9099-3522","observed_orcids":["https://orcid.org/0000-0002-9099-3522"]},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sj\u00f6lund, Jens","raw_affiliation_strings":["Department of Information Technology Uppsala University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology Uppsala University","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024256519","display_name":"Mikael Johansson","orcid":"https://orcid.org/0000-0002-2237-2580","observed_orcids":["https://orcid.org/0000-0002-2237-2580","https://orcid.org/0000-0001-7723-2801","https://orcid.org/0000-0002-2903-6301"]},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]},{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Johansson, Mikael","raw_affiliation_strings":["Department of Information Technology Uppsala University","Division of Decision and Control Systems KTH Royal Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology Uppsala University","institution_ids":["https://openalex.org/I123387679"]},{"raw_affiliation_string":"Division of Decision and Control Systems KTH Royal Institute of Technology","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0701,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.30723556,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9945999979972839,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9945999979972839,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.004800000227987766,"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":0.00019999999494757503,"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/hyperparameter-optimization","display_name":"hyperparameter optimization","score":0.9710000157356262},{"id":"https://openalex.org/keywords/adaptive-learning-rate","display_name":"adaptive learning rate","score":0.5320000052452087},{"id":"https://openalex.org/keywords/privacy-utility-trade-off","display_name":"privacy-utility trade-off","score":0.9300000071525574},{"id":"https://openalex.org/keywords/convergence-rate","display_name":"convergence rate","score":0.6919999718666077},{"id":"https://openalex.org/keywords/non-convex-loss-functions","display_name":"non-convex loss functions","score":0.800000011920929},{"id":"https://openalex.org/keywords/gradient-norm","display_name":"gradient norm","score":0.7720000147819519}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.8942999839782715},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.704800009727478},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6101999878883362},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6093999743461609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5562000274658203},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5325999855995178},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5253999829292297},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5160999894142151},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4494999945163727},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.4050000011920929},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4027999937534332},{"id":"https://openalex.org/C10494615","wikidata":"https://www.wikidata.org/wiki/Q17086765","display_name":"Proximal Gradient Methods","level":4,"score":0.38580000400543213},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3815000057220459},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.373199999332428},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.3560999929904938},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3425000011920929},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.3183000087738037},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3131999969482422},{"id":"https://openalex.org/C111110010","wikidata":"https://www.wikidata.org/wiki/Q2627315","display_name":"Convex combination","level":4,"score":0.310699999332428},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.29919999837875366},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:DiVA.org:uu-516854","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-516854","pdf_url":"https://uu.diva-portal.org/smash/get/diva2:1815963/FULLTEXT01","source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I86987016","host_organization_name":"KTH Royal Institute of Technology","host_organization_lineage":["https://openalex.org/I86987016"],"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":"pmh:oai:DiVA.org:uu-516854","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-516854","pdf_url":"https://uu.diva-portal.org/smash/get/diva2:1815963/FULLTEXT01","source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I86987016","host_organization_name":"KTH Royal Institute of Technology","host_organization_lineage":["https://openalex.org/I86987016"],"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"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322327","display_name":"Knut och Alice Wallenbergs Stiftelse","ror":"https://ror.org/004hzzk67"},{"id":"https://openalex.org/F4320322509","display_name":"Kungliga Tekniska H\u00f6gskolan","ror":"https://ror.org/026vcq606"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7054288083.pdf","grobid_xml":"https://content.openalex.org/works/W7054288083.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1932922755","https://openalex.org/W1985511977","https://openalex.org/W1992926795","https://openalex.org/W2001619934","https://openalex.org/W2002394060","https://openalex.org/W2112796928","https://openalex.org/W2296319761","https://openalex.org/W2927692314","https://openalex.org/W2946348439","https://openalex.org/W2948817437","https://openalex.org/W2964121744","https://openalex.org/W2964296660","https://openalex.org/W2998508934","https://openalex.org/W3119876694","https://openalex.org/W3128675832","https://openalex.org/W3175311566","https://openalex.org/W3209568007","https://openalex.org/W3213051863","https://openalex.org/W4205228770","https://openalex.org/W4283159449","https://openalex.org/W4292022450","https://openalex.org/W7133238482"],"related_works":["https://openalex.org/W3192751261","https://openalex.org/W3213051863","https://openalex.org/W4311795711","https://openalex.org/W3207569289","https://openalex.org/W7161058163","https://openalex.org/W4310630347","https://openalex.org/W7108220028","https://openalex.org/W3204117015","https://openalex.org/W2892102107","https://openalex.org/W4415082948"],"abstract_inverted_index":{"We":[0,53],"present":[1],"an":[2],"adaptive":[3],"mechanism":[4,22,56],"for":[5,57,73,83],"hyperparameter":[6,41],"selection":[7,42],"in":[8],"differentially":[9],"private":[10],"optimization":[11],"that":[12,40,48,106,123],"addresses":[13],"the":[14,24,36,50,74,84,87,97,113,124],"inherent":[15],"trade-off":[16],"between":[17],"utility":[18],"and":[19,27,34,64,77,90],"privacy.":[20],"The":[21],"eliminates":[23],"often":[25],"unstructured":[26],"time-consuming":[28],"manual":[29,135],"effort":[30],"of":[31,47,49,86,132],"selecting":[32],"hyperparameters":[33],"avoids":[35],"additional":[37],"privacy":[38],"costs":[39],"otherwise":[43],"incurs":[44],"on":[45,61],"top":[46],"actual":[51],"algorithm.":[52],"instantiate":[54],"our":[55],"noisy":[58,107],"gradient":[59,98,108],"descent":[60,109],"non-convex,":[62],"convex":[63,66],"strongly":[65],"loss":[67,88],"functions,":[68],"respectively,":[69],"to":[70,92],"derive":[71],"schedules":[72,81,125],"noise":[75],"variance":[76],"step":[78],"size.":[79],"These":[80],"account":[82],"properties":[85],"function":[89],"adapt":[91],"convergence":[93],"metrics":[94],"such":[95],"as":[96,116],"norm.":[99],"When":[100],"using":[101],"these":[102],"schedules,":[103],"we":[104],"show":[105,122],"converges":[110],"at":[111],"essentially":[112],"same":[114],"rate":[115],"its":[117],"noise-free":[118],"counterpart.":[119],"Numerical":[120],"experiments":[121],"consistently":[126],"perform":[127],"well":[128],"across":[129],"a":[130],"range":[131],"datasets":[133],"without":[134],"tuning.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}
