{"id":"https://openalex.org/W3192474509","doi":"https://doi.org/10.24963/ijcai.2021/560","title":"Stochastic Probing with Increasing Precision","display_name":"Stochastic Probing with Increasing Precision","publication_year":2021,"publication_date":"2021-08-01","ids":{"openalex":"https://openalex.org/W3192474509","doi":"https://doi.org/10.24963/ijcai.2021/560","mag":"3192474509"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2021/560","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/560","pdf_url":"https://www.ijcai.org/proceedings/2021/0560.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2021/0560.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065332233","display_name":"Martin Hoefer","orcid":"https://orcid.org/0000-0003-0131-5605"},"institutions":[{"id":"https://openalex.org/I114090438","display_name":"Goethe University Frankfurt","ror":"https://ror.org/04cvxnb49","country_code":"DE","type":"education","lineage":["https://openalex.org/I114090438"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Hoefer","raw_affiliation_strings":["Goethe University Frankfurt","Goethe University Frankfurt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Goethe University Frankfurt","institution_ids":["https://openalex.org/I114090438"]},{"raw_affiliation_string":"Goethe University Frankfurt, Germany","institution_ids":["https://openalex.org/I114090438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056422606","display_name":"Kevin Schewior","orcid":"https://orcid.org/0000-0003-2236-0210"},"institutions":[{"id":"https://openalex.org/I180923762","display_name":"University of Cologne","ror":"https://ror.org/00rcxh774","country_code":"DE","type":"education","lineage":["https://openalex.org/I180923762"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kevin Schewior","raw_affiliation_strings":["University of Cologne","University of Cologne, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cologne","institution_ids":["https://openalex.org/I180923762"]},{"raw_affiliation_string":"University of Cologne, Germany","institution_ids":["https://openalex.org/I180923762"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087608313","display_name":"Daniel Schmand","orcid":"https://orcid.org/0000-0001-7776-3426"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Schmand","raw_affiliation_strings":["University of Bremen","University of Bremen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen","institution_ids":["https://openalex.org/I180437899"]},{"raw_affiliation_string":"University of Bremen, Germany","institution_ids":["https://openalex.org/I180437899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13577207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4069","last_page":"4075"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9991999864578247,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9983999729156494,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/realization","display_name":"Realization (probability)","score":0.8073024153709412},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.6193341612815857},{"id":"https://openalex.org/keywords/expected-value","display_name":"Expected value","score":0.5760499238967896},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5752081871032715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5721088647842407},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.5384634733200073},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5108048915863037},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.48657429218292236},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.48385536670684814},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4201594889163971},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4056106209754944},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3791669011116028},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2310906946659088},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18115228414535522},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11903038620948792},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.10799124836921692}],"concepts":[{"id":"https://openalex.org/C2781089630","wikidata":"https://www.wikidata.org/wiki/Q21856745","display_name":"Realization (probability)","level":2,"score":0.8073024153709412},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.6193341612815857},{"id":"https://openalex.org/C141042865","wikidata":"https://www.wikidata.org/wiki/Q200125","display_name":"Expected value","level":2,"score":0.5760499238967896},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5752081871032715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5721088647842407},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.5384634733200073},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5108048915863037},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48657429218292236},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.48385536670684814},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4201594889163971},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4056106209754944},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3791669011116028},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2310906946659088},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18115228414535522},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11903038620948792},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.10799124836921692},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2021/560","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/560","pdf_url":"https://www.ijcai.org/proceedings/2021/0560.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:sdu.dk:openaire_cris_publications/ecaca689-b221-4f37-985f-103cd31c699e","is_oa":false,"landing_page_url":"https://portal.findresearcher.sdu.dk/da/publications/ecaca689-b221-4f37-985f-103cd31c699e","pdf_url":null,"source":{"id":"https://openalex.org/S4306400423","display_name":"University of Southern Denmark Research Portal (University of Southern Denmark)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177969490","host_organization_name":"University of Southern Denmark","host_organization_lineage":["https://openalex.org/I177969490"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Hoefer , M , Schewior , K &amp; Schmand , D 2024 , ' Stochastic Probing with Increasing Precision ' , SIAM Journal on Discrete Mathematics , vol. 38 , no. 1 , pp. 148-169 . https://doi.org/10.1137/22M149466X","raw_type":"article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2021/560","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2021/560","pdf_url":"https://www.ijcai.org/proceedings/2021/0560.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3192474509.pdf","grobid_xml":"https://content.openalex.org/works/W3192474509.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1500676409","https://openalex.org/W1788659242","https://openalex.org/W1909971775","https://openalex.org/W1984877922","https://openalex.org/W1996837595","https://openalex.org/W2034828004","https://openalex.org/W2041025394","https://openalex.org/W2136127899","https://openalex.org/W2149744080","https://openalex.org/W2152854599","https://openalex.org/W2179880041","https://openalex.org/W2262893750","https://openalex.org/W2503665996","https://openalex.org/W2593364751","https://openalex.org/W2751862591","https://openalex.org/W2758521565","https://openalex.org/W2787518409","https://openalex.org/W2804453093","https://openalex.org/W2909224348","https://openalex.org/W2915662027","https://openalex.org/W2942840423","https://openalex.org/W2950397526","https://openalex.org/W2950535090","https://openalex.org/W2963159830","https://openalex.org/W2963230391","https://openalex.org/W3041225824","https://openalex.org/W3125634603","https://openalex.org/W4240196045","https://openalex.org/W4245298853","https://openalex.org/W4300353561","https://openalex.org/W4302517748"],"related_works":["https://openalex.org/W2766238494","https://openalex.org/W2097390272","https://openalex.org/W1802643016","https://openalex.org/W1964917647","https://openalex.org/W2100521573","https://openalex.org/W847339734","https://openalex.org/W1523494361","https://openalex.org/W2105067139","https://openalex.org/W2017311532","https://openalex.org/W1930446896"],"abstract_inverted_index":{"We":[0,44,112],"consider":[1],"a":[2,10,46,86],"selection":[3],"problem":[4],"with":[5,123],"stochastic":[6],"probing.":[7],"There":[8,84],"is":[9,58,82,85,95],"set":[11],"of":[12,41,65,89,108],"items":[13],"whose":[14],"values":[15],"are":[16,23],"drawn":[17],"from":[18],"independent":[19],"distributions.":[20],"The":[21],"distributions":[22,118],"known":[24],"in":[25,78,127],"advance.":[26],"Each":[27,33],"item":[28],"can":[29],"be":[30],"\\emph{tested}":[31],"repeatedly.":[32],"test":[34,52],"reduces":[35],"the":[36,39,50,55,63,66,76,80,105,109],"uncertainty":[37],"about":[38],"realization":[40,81],"its":[42],"value.":[43],"study":[45,113],"testing":[47,99],"model,":[48],"where":[49],"first":[51],"reveals":[53],"if":[54],"realized":[56],"value":[57,107],"smaller":[59],"or":[60],"larger":[61],"than":[62],"median":[64],"underlying":[67],"distribution.":[68],"Subsequent":[69],"tests":[70],"allow":[71,102],"to":[72,96,103],"further":[73],"narrow":[74],"down":[75],"interval":[77],"which":[79],"located.":[83],"limited":[87],"number":[88],"possible":[90],"tests,":[91],"and":[92,116,119],"our":[93],"goal":[94],"design":[97],"near-optimal":[98],"strategies":[100],"that":[101],"maximize":[104],"expected":[106],"chosen":[110],"item.":[111],"both":[114,128],"identical":[115],"non-identical":[117],"develop":[120],"polynomial-time":[121],"algorithms":[122],"constant":[124],"approximation":[125],"factors":[126],"scenarios.":[129]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
