{"id":"https://openalex.org/W7214016276","doi":"https://doi.org/10.48550/arxiv.2609.24496","title":"Conformalized Safe Feasible Sets in Uncertain Decision Systems","display_name":"Conformalized Safe Feasible Sets in Uncertain Decision Systems","publication_year":2026,"publication_date":"2026-09-21","ids":{"openalex":"https://openalex.org/W7214016276","doi":"https://doi.org/10.48550/arxiv.2609.24496"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.24496","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.24496","pdf_url":"https://arxiv.org/pdf/2609.24496","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/2609.24496","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130603533","display_name":"Yajie Bao","orcid":null,"observed_orcids":[]},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bao, Yajie","raw_affiliation_strings":["School of Management , Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management , Fudan University","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125717378","display_name":"Yinjie Min","orcid":"https://orcid.org/0009-0009-3487-9360","observed_orcids":["https://orcid.org/0009-0009-3487-9360"]},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min, Yinjie","raw_affiliation_strings":["School of Statistics and Data Science , Nankai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Data Science , Nankai University","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130541844","display_name":"Haojie Ren","orcid":"https://orcid.org/0009-0006-0019-0950","observed_orcids":["https://orcid.org/0009-0006-0019-0950"]},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ren, Haojie","raw_affiliation_strings":["School of Mathematical Sciences , Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences , Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136051807","display_name":"Changliang Zou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zou, Changliang","raw_affiliation_strings":["School of Statistics and Data Science , Nankai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics and Data Science , Nankai University","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"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/T10142","display_name":"Formal Methods in Verification","score":0.2761000096797943,"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/T10142","display_name":"Formal Methods in Verification","score":0.2761000096797943,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.1688999980688095,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.09300000220537186,"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/conformal-prediction","display_name":"conformal prediction","score":0.871999979019165}],"concepts":[{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5794000029563904},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5752000212669373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5267999768257141},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.48350000381469727},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.47350001335144043},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40119999647140503},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.38679999113082886},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36739999055862427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36629998683929443},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C130648207","wikidata":"https://www.wikidata.org/wiki/Q6007562","display_name":"Imprecise probability","level":3,"score":0.33570000529289246},{"id":"https://openalex.org/C115988155","wikidata":"https://www.wikidata.org/wiki/Q3262192","display_name":"Decision problem","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C150325174","wikidata":"https://www.wikidata.org/wiki/Q4335500","display_name":"Optimal decision","level":3,"score":0.301800012588501},{"id":"https://openalex.org/C2780267512","wikidata":"https://www.wikidata.org/wiki/Q6997828","display_name":"Nestedness","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C59594135","wikidata":"https://www.wikidata.org/wiki/Q5249242","display_name":"Decision model","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C28901747","wikidata":"https://www.wikidata.org/wiki/Q177571","display_name":"Decision theory","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.24496","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.24496","pdf_url":"https://arxiv.org/pdf/2609.24496","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":"doi:10.48550/arxiv.2609.24496","doi":"https://doi.org/10.48550/arxiv.2609.24496","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.24496","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.24496","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.24496","pdf_url":"https://arxiv.org/pdf/2609.24496","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":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214016276.pdf","grobid_xml":"https://content.openalex.org/works/W7214016276.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W4391801072"],"related_works":["https://openalex.org/W4407186934","https://openalex.org/W7124713836","https://openalex.org/W7163701558","https://openalex.org/W4403852112","https://openalex.org/W7140075586","https://openalex.org/W7160923456","https://openalex.org/W4387724540","https://openalex.org/W7214053638","https://openalex.org/W3206245963","https://openalex.org/W3166452030"],"abstract_inverted_index":{"Safety-critical":[0],"decision":[1,199],"systems":[2],"often":[3],"require":[4],"a":[5,22,30,51,75,89,106,111,154,169],"downstream":[6],"optimizer":[7],"to":[8,28,105],"choose":[9],"from":[10],"an":[11,17,144],"unknown":[12],"feasible":[13,38,117,141,171,212],"set":[14,39,53,80,142,162,172],"determined":[15],"by":[16,101,176],"unobserved":[18,56],"label":[19,57],"$Y$.":[20],"Given":[21,110],"context":[23],"$X$,":[24],"the":[25,36,55,95,124,130,139,177,205],"goal":[26],"is":[27,133],"construct":[29,50],"safe":[31,64,140,170],"subset":[32,132,192],"$D(X)$":[33],"contained":[34,134],"in":[35,68,135],"oracle":[37],"$A(X,Y)$":[40],"with":[41],"probability":[42,96],"at":[43,128,147],"least":[44],"$1-\u03b1$.":[45],"Existing":[46],"conformal":[47,90],"approaches":[48],"typically":[49],"prediction":[52],"of":[54,97,115],"$Y$":[58],"and":[59,137,187,197],"retain":[60],"decisions":[61],"that":[62,92,166,174,202],"are":[63],"for":[65,190],"every":[66],"value":[67],"this":[69,73,98,152],"set.":[70],"Although":[71],"valid,":[72],"requires":[74],"stronger":[76],"intermediate":[77],"event":[78,100],"than":[79],"inclusion.":[81],"We":[82,181],"propose":[83],"Directed":[84],"Inclusion":[85],"Safety":[86],"Calibration":[87],"(DISC),":[88],"framework":[91],"directly":[93],"controls":[94],"inclusion":[99,157,207],"reducing":[102],"its":[103],"verification":[104],"scalar":[107],"critical-inclusion":[108],"score.":[109],"pretrained":[112],"nested":[113],"family":[114],"candidate":[116],"sets,":[118],"DISC":[119,167,203],"assigns":[120],"each":[121],"labeled":[122],"observation":[123],"smallest":[125],"nestedness":[126],"level":[127],"which":[129],"corresponding":[131,178],"$A(X,Y)$,":[136],"constructs":[138],"using":[143],"empirical":[145],"quantile":[146],"test-time.":[148],"With":[149],"data":[150],"exchangeability,":[151],"yields":[153],"finite-sample,":[155],"distribution-free":[156],"guarantee.":[158],"Under":[159],"two":[160],"practical":[161],"families,":[163],"we":[164],"show":[165,201],"produces":[168],"containing":[173],"obtained":[175],"calibration":[179],"baseline.":[180],"further":[182],"develop":[183],"optimization-based":[184],"score":[185],"computation":[186],"decision-aware":[188],"procedures":[189],"learning":[191],"families.":[193],"Experiments":[194],"across":[195],"continuous":[196],"structured":[198],"problems":[200],"achieves":[204],"target":[206],"guarantee":[208],"while":[209],"producing":[210],"larger":[211],"regions.":[213]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-23T00:00:00"}
