{"id":"https://openalex.org/W2462738568","doi":"https://doi.org/10.1109/tit.2017.2760634","title":"Unequal Error Protection Querying Policies for the Noisy 20 Questions Problem","display_name":"Unequal Error Protection Querying Policies for the Noisy 20 Questions Problem","publication_year":2017,"publication_date":"2017-10-06","ids":{"openalex":"https://openalex.org/W2462738568","doi":"https://doi.org/10.1109/tit.2017.2760634","mag":"2462738568"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2017.2760634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2017.2760634","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Theory","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1606.09233","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hye Won Chung","orcid":"https://orcid.org/0000-0002-8947-9956"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hye Won Chung","raw_affiliation_strings":["School of Electrical Engineering, KAIST, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-8947-9956","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Brian M. Sadler","orcid":null},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian M. Sadler","raw_affiliation_strings":["U.S. Army Research Laboratory, Adelphi, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"U.S. Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lizhong Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lizhong Zheng","raw_affiliation_strings":["EECS Department, Massachusetts Institute of Technology, Cambridge, MA, 3USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS Department, Massachusetts Institute of Technology, Cambridge, MA, 3USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":null,"display_name":"Alfred O. Hero","orcid":"https://orcid.org/0000-0002-2531-9670"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alfred O. Hero","raw_affiliation_strings":["EECS Department, University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-2531-9670","affiliations":[{"raw_affiliation_string":"EECS Department, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":1.0393,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82240198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"64","issue":"2","first_page":"1105","last_page":"1131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.8474000096321106,"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":0.8474000096321106,"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/T11269","display_name":"Algorithms and Data Compression","score":0.04259999841451645,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.013799999840557575,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.6050999760627747},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.5634999871253967},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5070000290870667},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.4537999927997589},{"id":"https://openalex.org/keywords/superposition-principle","display_name":"Superposition principle","score":0.4343000054359436},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.43380001187324524},{"id":"https://openalex.org/keywords/block-code","display_name":"Block code","score":0.42669999599456787},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4212000072002411},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.38999998569488525},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.375900000333786}],"concepts":[{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6050999760627747},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.5634999871253967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5609999895095825},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.560699999332428},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5070000290870667},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5054000020027161},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.4537999927997589},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.439300000667572},{"id":"https://openalex.org/C27753989","wikidata":"https://www.wikidata.org/wiki/Q284885","display_name":"Superposition principle","level":2,"score":0.4343000054359436},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"score":0.42669999599456787},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.38999998569488525},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C173988684","wikidata":"https://www.wikidata.org/wiki/Q863510","display_name":"Binary symmetric channel","level":4,"score":0.3702999949455261},{"id":"https://openalex.org/C92224547","wikidata":"https://www.wikidata.org/wiki/Q1673216","display_name":"Probability of error","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C55974624","wikidata":"https://www.wikidata.org/wiki/Q1188504","display_name":"Exponential family","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C166366890","wikidata":"https://www.wikidata.org/wiki/Q602136","display_name":"Channel code","level":3,"score":0.33970001339912415},{"id":"https://openalex.org/C2780388253","wikidata":"https://www.wikidata.org/wiki/Q5421508","display_name":"Exponent","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3264999985694885},{"id":"https://openalex.org/C128040838","wikidata":"https://www.wikidata.org/wiki/Q1810628","display_name":"Pseudorandom binary sequence","level":3,"score":0.3239000141620636},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C75235859","wikidata":"https://www.wikidata.org/wiki/Q582659","display_name":"Exponential growth","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.27649998664855957},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.27250000834465027},{"id":"https://openalex.org/C206468330","wikidata":"https://www.wikidata.org/wiki/Q834373","display_name":"Code rate","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C141042865","wikidata":"https://www.wikidata.org/wiki/Q200125","display_name":"Expected value","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tit.2017.2760634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2017.2760634","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Theory","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1606.09233","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1606.09233","pdf_url":"https://arxiv.org/pdf/1606.09233","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1606.09233","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1606.09233","pdf_url":"https://arxiv.org/pdf/1606.09233","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8346236733","display_name":null,"funder_award_id":"W911NF-15-1-0479","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G932903589","display_name":null,"funder_award_id":"W911NF-11-1-0391","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W55403181","https://openalex.org/W1981602306","https://openalex.org/W1995875735","https://openalex.org/W2040877654","https://openalex.org/W2062626064","https://openalex.org/W2076580309","https://openalex.org/W2079976550","https://openalex.org/W2115305054","https://openalex.org/W2134619286","https://openalex.org/W2136817255","https://openalex.org/W2296441616","https://openalex.org/W2507539979","https://openalex.org/W2962728086","https://openalex.org/W6633640631","https://openalex.org/W6756615331"],"related_works":[],"abstract_inverted_index":{"In":[0,20],"this":[1,21],"paper,":[2],"we":[3],"propose":[4],"an":[5,29,79,107],"open-loop":[6],"unequal-error-protection":[7],"querying":[8,93,132],"policy":[9],"based":[10,95],"on":[11,96],"superposition":[12,98],"coding":[13,84,99,122],"for":[14],"the":[15,32,48,58,64,71,119,130,134,140,145,158,163],"noisy":[16,45,59],"20":[17,72],"questions":[18,73],"problem.":[19],"problem,":[22],"a":[23,35,54,67,148],"player":[24],"wishes":[25],"to":[26,78],"successively":[27],"refine":[28],"estimate":[30],"of":[31,34,66,82,110,118,136,142,147,160,172],"value":[33],"continuous":[36],"random":[37,173],"variable":[38],"by":[39,124],"posing":[40],"binary":[41,68],"queries":[42,49,143,153],"and":[43,57],"receiving":[44],"responses.":[46],"When":[47],"are":[50,61,154],"designed":[51,156],"non-adaptively":[52],"as":[53,63],"single":[55],"block":[56,174],"responses":[60],"modeled":[62],"output":[65],"symmetric":[69],"channel,":[70],"problem":[74,81],"can":[75],"be":[76],"mapped":[77],"equivalent":[80],"channel":[83],"with":[85,106,157],"unequal":[86],"error":[87,104,165,178],"protection":[88],"(UEP).":[89],"A":[90],"new":[91],"non-adaptive":[92],"strategy":[94],"UEP":[97,120],"is":[100,113,167],"introduced,":[101],"whose":[102],"estimation":[103],"decreases":[105],"exponential":[108,137],"rate":[109,135,146],"convergence":[111],"that":[112,117,171],"significantly":[114,168],"better":[115,169],"than":[116,170],"repetition":[121],"introduced":[123],"Variani":[125],"et":[126],"al.":[127],"(2015).":[128],"With":[129],"proposed":[131],"strategy,":[133],"decrease":[138],"in":[139],"number":[141],"matches":[144],"closed-loop":[149],"adaptive":[150],"scheme,":[151],"where":[152],"sequentially":[155],"benefit":[159],"feedback.":[161],"Furthermore,":[162],"achievable":[164],"exponent":[166],"codes":[175],"employing":[176],"equal":[177],"protection.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-07-22T00:00:00"}