{"id":"https://openalex.org/W2922995562","doi":"https://doi.org/10.1109/cdc40024.2019.9029477","title":"Semi-Parametric Uncertainty Bounds for Binary Classification","display_name":"Semi-Parametric Uncertainty Bounds for Binary Classification","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2922995562","doi":"https://doi.org/10.1109/cdc40024.2019.9029477","mag":"2922995562"},"language":"en","primary_location":{"id":"doi:10.1109/cdc40024.2019.9029477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1903.09790","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016151972","display_name":"Bal\u00e1zs Csan\u00e1d Cs\u00e1ji","orcid":"https://orcid.org/0000-0001-7079-8343"},"institutions":[{"id":"https://openalex.org/I7597260","display_name":"Hungarian Academy of Sciences","ror":"https://ror.org/02ks8qq67","country_code":"HU","type":"funder","lineage":["https://openalex.org/I7597260"]},{"id":"https://openalex.org/I4210117195","display_name":"Institute for Computer Science and Control","ror":"https://ror.org/0249v7n71","country_code":"HU","type":"facility","lineage":["https://openalex.org/I4210117195","https://openalex.org/I7597260"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Balazs Csanad Csaji","raw_affiliation_strings":["MTA SZTAKI: The Institute for Computer Science and Control, Hungarian Academy of Sciences, Budapest, Hungary","Hungarian Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"MTA SZTAKI: The Institute for Computer Science and Control, Hungarian Academy of Sciences, Budapest, Hungary","institution_ids":["https://openalex.org/I4210117195","https://openalex.org/I7597260"]},{"raw_affiliation_string":"Hungarian Academy of Sciences","institution_ids":["https://openalex.org/I7597260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060138306","display_name":"Ambrus Tam\u00e1s","orcid":"https://orcid.org/0000-0002-6049-4626"},"institutions":[{"id":"https://openalex.org/I7597260","display_name":"Hungarian Academy of Sciences","ror":"https://ror.org/02ks8qq67","country_code":"HU","type":"funder","lineage":["https://openalex.org/I7597260"]},{"id":"https://openalex.org/I4210117195","display_name":"Institute for Computer Science and Control","ror":"https://ror.org/0249v7n71","country_code":"HU","type":"facility","lineage":["https://openalex.org/I4210117195","https://openalex.org/I7597260"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Ambrus Tamas","raw_affiliation_strings":["MTA SZTAKI: The Institute for Computer Science and Control, Hungarian Academy of Sciences, Budapest, Hungary","Hungarian Academy of Sciences,MTA SZTAKI: The Institute for Computer Science and Control,Budapest,Hungary"],"affiliations":[{"raw_affiliation_string":"MTA SZTAKI: The Institute for Computer Science and Control, Hungarian Academy of Sciences, Budapest, Hungary","institution_ids":["https://openalex.org/I4210117195","https://openalex.org/I7597260"]},{"raw_affiliation_string":"Hungarian Academy of Sciences,MTA SZTAKI: The Institute for Computer Science and Control,Budapest,Hungary","institution_ids":["https://openalex.org/I4210117195","https://openalex.org/I7597260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016151972"],"corresponding_institution_ids":["https://openalex.org/I4210117195","https://openalex.org/I7597260"],"apc_list":null,"apc_paid":null,"fwci":0.24,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55175164,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4427","last_page":"4432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/resampling","display_name":"Resampling","score":0.7268872261047363},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.6534144282341003},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5823302865028381},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.49630099534988403},{"id":"https://openalex.org/keywords/kernel-regression","display_name":"Kernel regression","score":0.45928311347961426},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4485902190208435},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4384477436542511},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4363905191421509},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4179137349128723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4043721556663513},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.40204426646232605},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.22286710143089294},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.21311187744140625}],"concepts":[{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.7268872261047363},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.6534144282341003},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5823302865028381},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49630099534988403},{"id":"https://openalex.org/C200695384","wikidata":"https://www.wikidata.org/wiki/Q1739319","display_name":"Kernel regression","level":3,"score":0.45928311347961426},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4485902190208435},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4384477436542511},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4363905191421509},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4179137349128723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4043721556663513},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.40204426646232605},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.22286710143089294},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.21311187744140625},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/cdc40024.2019.9029477","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1903.09790","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.09790","pdf_url":"https://arxiv.org/pdf/1903.09790","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"","raw_type":"text"},{"id":"mag:2922995562","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1903.09790v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:eprints.sztaki.hu:9873","is_oa":false,"landing_page_url":"http://eprints.sztaki.hu/9873/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401907","display_name":"SZTAKI Publication Repository (Hungarian Academy of Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I7597260","host_organization_name":"Hungarian Academy of Sciences","host_organization_lineage":["https://openalex.org/I7597260"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Book Section"},{"id":"doi:10.48550/arxiv.1903.09790","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1903.09790","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1903.09790","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.09790","pdf_url":"https://arxiv.org/pdf/1903.09790","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2922995562.pdf","grobid_xml":"https://content.openalex.org/works/W2922995562.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W592973865","https://openalex.org/W1484867920","https://openalex.org/W1986280275","https://openalex.org/W2017170340","https://openalex.org/W2066065052","https://openalex.org/W2148603752","https://openalex.org/W2168029744","https://openalex.org/W2255898239","https://openalex.org/W2418306335","https://openalex.org/W2624060266","https://openalex.org/W2733092977","https://openalex.org/W2897788210","https://openalex.org/W3101183984","https://openalex.org/W3101749733"],"related_works":["https://openalex.org/W1578660008","https://openalex.org/W3099728509","https://openalex.org/W2730059782","https://openalex.org/W2964175492","https://openalex.org/W3088268199","https://openalex.org/W2138805387","https://openalex.org/W3039471369","https://openalex.org/W3122962384","https://openalex.org/W2241196281","https://openalex.org/W3082557888","https://openalex.org/W2962789209","https://openalex.org/W3031848966","https://openalex.org/W2613095180","https://openalex.org/W2598307405","https://openalex.org/W2985079138","https://openalex.org/W2963629082","https://openalex.org/W2944981336","https://openalex.org/W2987189410","https://openalex.org/W1916318312","https://openalex.org/W2416563375"],"abstract_inverted_index":{"The":[0,25],"paper":[1],"studies":[2],"binary":[3],"classification":[4],"and":[5,61,78],"aims":[6],"at":[7,52],"estimating":[8],"the":[9,15,19,23,29,33,46,58],"underlying":[10],"regression":[11,26,59],"function":[12,27,60],"which":[13],"is":[14,28],"conditional":[16],"expectation":[17],"of":[18,32,48,69],"class":[20],"labels":[21],"given":[22],"inputs.":[24],"key":[30],"component":[31],"Bayes":[34],"optimal":[35,40],"classifier,":[36],"moreover,":[37],"besides":[38],"providing":[39],"predictions,":[41],"it":[42],"can":[43],"also":[44],"assess":[45],"risk":[47],"misclassification.":[49],"We":[50],"aim":[51],"building":[53],"non-asymptotic":[54],"confidence":[55,72],"regions":[56,73],"for":[57],"suggest":[62],"three":[63],"kernel-based":[64],"semi-parametric":[65],"resampling":[66],"methods.":[67],"All":[68],"them":[70],"guarantee":[71],"with":[74],"exact":[75],"coverage":[76],"probabilities":[77],"they":[79],"are":[80],"strongly":[81],"consistent.":[82]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
