{"id":"https://openalex.org/W2996766289","doi":"https://doi.org/10.48550/arxiv.2001.00106","title":"PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction","display_name":"PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction","publication_year":2019,"publication_date":"2019-12-31","ids":{"openalex":"https://openalex.org/W2996766289","doi":"https://doi.org/10.48550/arxiv.2001.00106","mag":"2996766289"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2001.00106","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.00106","pdf_url":"https://arxiv.org/pdf/2001.00106","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2001.00106","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014443062","display_name":"Sangdon Park","orcid":"https://orcid.org/0000-0001-5392-749X","observed_orcids":["https://orcid.org/0000-0001-5392-749X"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Park, Sangdon","raw_affiliation_strings":["University of Pennsylvania","#N#               * University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029243071","display_name":"Osbert Bastani","orcid":"https://orcid.org/0000-0001-9990-7566","observed_orcids":["https://orcid.org/0000-0001-9990-7566"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bastani, Osbert","raw_affiliation_strings":["University of Pennsylvania","#N#               * University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052941508","display_name":"Nikolai Matni","orcid":"https://orcid.org/0000-0003-4936-3921","observed_orcids":["https://orcid.org/0000-0003-4936-3921"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matni, Nikolai","raw_affiliation_strings":["University of Pennsylvania","#N#               * University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030456600","display_name":"Insup Lee","orcid":"https://orcid.org/0000-0003-2672-1132","observed_orcids":["https://orcid.org/0000-0003-2672-1132","https://orcid.org/0000-0002-9822-9860"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lee, Insup","raw_affiliation_strings":["University of Pennsylvania","#N#               * University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.3163999915122986,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.3163999915122986,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.2824999988079071,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.11649999767541885,"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/deep-neural-network","display_name":"deep neural network","score":0.8399999737739563},{"id":"https://openalex.org/keywords/generalization-bounds","display_name":"generalization bounds","score":0.9850000143051147},{"id":"https://openalex.org/keywords/learning-theory","display_name":"learning theory","score":0.5870000123977661},{"id":"https://openalex.org/keywords/resnet","display_name":"ResNet","score":0.8159999847412109},{"id":"https://openalex.org/keywords/imagenet","display_name":"ImageNet","score":0.875},{"id":"https://openalex.org/keywords/visual-tracking","display_name":"visual object tracking","score":0.9100000262260437},{"id":"https://openalex.org/keywords/dynamics-model","display_name":"dynamics model","score":0.6439999938011169},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.9679999947547913}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.763958752155304},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.7474328875541687},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.737159252166748},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6782711744308472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6540076732635498},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6322169303894043},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5800907015800476},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5256684422492981},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.48358434438705444},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4769945740699768},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15369871258735657},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"pmh:oai:arXiv.org:2001.00106","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.00106","pdf_url":"https://arxiv.org/pdf/2001.00106","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},{"id":"pmh:oai:repository.upenn.edu:cis_papers-1905","doi":null,"is_oa":true,"landing_page_url":"https://repository.upenn.edu/cgi/viewcontent.cgi?article=1905&context=cis_papers","pdf_url":"https://repository.upenn.edu/cgi/viewcontent.cgi?article=1905&context=cis_papers","source":{"id":"https://openalex.org/S4377196331","display_name":"Scholarly Commons (University of Pennsylvania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79576946","host_organization_name":"University of Pennsylvania","host_organization_lineage":["https://openalex.org/I79576946"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Departmental Papers (CIS)","raw_type":"text"},{"id":"mag:2996766289","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2001.00106","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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:repository.upenn.edu:20.500.14332/6939","doi":null,"is_oa":false,"landing_page_url":"https://repository.upenn.edu/handle/20.500.14332/6939","pdf_url":null,"source":{"id":"https://openalex.org/S4306402083","display_name":"ScholarlyCommons (University of Pennsylvania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79576946","host_organization_name":"University of Pennsylvania","host_organization_lineage":["https://openalex.org/I79576946"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"published","raw_type":"Presentation"},{"id":"doi:10.48550/arxiv.2001.00106","doi":"https://doi.org/10.48550/arxiv.2001.00106","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2001.00106","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2001.00106","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.00106","pdf_url":"https://arxiv.org/pdf/2001.00106","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3345105982","display_name":null,"funder_award_id":"FA8750-18-C-0090","funder_id":"https://openalex.org/F4320338294","funder_display_name":"Air Force Research Laboratory"},{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5057914180","display_name":null,"funder_award_id":"FA8750- 18-C-0090","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G6901837805","display_name":"SHF: Small: Inferring Specifications for Blackbox Code","funder_award_id":"1910769","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"},{"id":"https://openalex.org/F4320306078","display_name":"U.S. Department of Defense","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320332815","display_name":"Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2996766289.pdf","grobid_xml":"https://content.openalex.org/works/W2996766289.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1481566577","https://openalex.org/W1520252399","https://openalex.org/W1521746852","https://openalex.org/W1598033630","https://openalex.org/W1598866093","https://openalex.org/W1599263113","https://openalex.org/W1618905105","https://openalex.org/W1960174506","https://openalex.org/W1986593852","https://openalex.org/W2012942264","https://openalex.org/W2019363670","https://openalex.org/W2056597459","https://openalex.org/W2089961441","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2149298154","https://openalex.org/W2166693382","https://openalex.org/W2188631158","https://openalex.org/W2194775991","https://openalex.org/W2254249950","https://openalex.org/W2275716410","https://openalex.org/W2340000481","https://openalex.org/W2597787948","https://openalex.org/W2606051733","https://openalex.org/W2618318883","https://openalex.org/W2626967530","https://openalex.org/W2788433952","https://openalex.org/W2810469995","https://openalex.org/W2891009102","https://openalex.org/W2943913950","https://openalex.org/W2944847804","https://openalex.org/W2950220847","https://openalex.org/W2963185791","https://openalex.org/W2963619356","https://openalex.org/W2963960193","https://openalex.org/W2964153729"],"related_works":["https://openalex.org/W2892888874","https://openalex.org/W2923702720","https://openalex.org/W3095327551","https://openalex.org/W2902494765","https://openalex.org/W2737498590","https://openalex.org/W3035059588","https://openalex.org/W7221524471","https://openalex.org/W7067273407","https://openalex.org/W4395669171","https://openalex.org/W7057095879"],"abstract_inverted_index":{"We":[0,38],"propose":[1],"an":[2],"algorithm":[3],"combining":[4],"calibrated":[5],"prediction":[6],"and":[7,60],"generalization":[8],"bounds":[9],"from":[10],"learning":[11,68],"theory":[12],"to":[13,46],"construct":[14,47],"confidence":[15,25,49],"sets":[16,50],"for":[17,27,53,64],"deep":[18],"neural":[19],"networks":[20],"with":[21,35],"PAC":[22,48],"guarantees---i.e.,":[23],"the":[24,32,65],"set":[26],"a":[28,55,61],"given":[29],"input":[30],"contains":[31],"true":[33],"label":[34],"high":[36],"probability.":[37],"demonstrate":[39],"how":[40],"our":[41],"approach":[42],"can":[43],"be":[44],"used":[45],"on":[51],"ResNet":[52],"ImageNet,":[54],"visual":[56],"object":[57],"tracking":[58],"model,":[59],"dynamics":[62],"model":[63],"half-cheetah":[66],"reinforcement":[67],"problem.":[69]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2020-01-10T00:00:00"}
