{"id":"https://openalex.org/W2139057562","doi":"https://doi.org/10.1109/tit.2011.2132550","title":"Large Deviation Bounds for Functionals of Viterbi Paths","display_name":"Large Deviation Bounds for Functionals of Viterbi Paths","publication_year":2011,"publication_date":"2011-05-25","ids":{"openalex":"https://openalex.org/W2139057562","doi":"https://doi.org/10.1109/tit.2011.2132550","mag":"2139057562"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2011.2132550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2011.2132550","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":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073581499","display_name":"Arka P. Ghosh","orcid":"https://orcid.org/0000-0002-6598-7788"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arka P. Ghosh","raw_affiliation_strings":["Departments of Statistics and Mathematics, Iowa State University, Ames, IA, USA","Depts. of Stat. & Math., Iowa State Univ., Ames, IA, USA"],"affiliations":[{"raw_affiliation_string":"Departments of Statistics and Mathematics, Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"Depts. of Stat. & Math., Iowa State Univ., Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029626515","display_name":"Elizabeth Kleiman","orcid":null},"institutions":[{"id":"https://openalex.org/I198796369","display_name":"Mount Mercy University","ror":"https://ror.org/02e891h43","country_code":"US","type":"education","lineage":["https://openalex.org/I198796369"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elizabeth Kleiman","raw_affiliation_strings":["Department of Computer Science, Mount Mercy University, Cedar Rapids, IA, USA","Dept. of Comput. Sci., Mount Mercy Univ., Cedar Rapids, IA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Mount Mercy University, Cedar Rapids, IA, USA","institution_ids":["https://openalex.org/I198796369"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Mount Mercy Univ., Cedar Rapids, IA, USA","institution_ids":["https://openalex.org/I198796369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030018417","display_name":"Alexander Roitershtein","orcid":"https://orcid.org/0000-0001-8207-4289"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Roitershtein","raw_affiliation_strings":["Department of Mathematics, Iowa State University, Ames, IA, USA","Dept. of Math., Iowa State Univ., Ames, IA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]},{"raw_affiliation_string":"Dept. of Math., Iowa State Univ., Ames, IA, USA#TAB#","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073581499"],"corresponding_institution_ids":["https://openalex.org/I173911158"],"apc_list":null,"apc_paid":null,"fwci":1.3157,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84890218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"57","issue":"6","first_page":"3932","last_page":"3937"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9994999766349792,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9994999766349792,"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":0.998199999332428,"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":0.9980000257492065,"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/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.900291383266449},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6515369415283203},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5969277024269104},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5413960218429565},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5376424193382263},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49939918518066406},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.49066293239593506},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4890356957912445},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.48232099413871765},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4648778438568115},{"id":"https://openalex.org/keywords/stochastic-process","display_name":"Stochastic process","score":0.46320095658302307},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.45924240350723267},{"id":"https://openalex.org/keywords/finite-state","display_name":"Finite state","score":0.45013538002967834},{"id":"https://openalex.org/keywords/forward-algorithm","display_name":"Forward algorithm","score":0.44926732778549194},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4411775469779968},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.426461786031723},{"id":"https://openalex.org/keywords/viterbi-decoder","display_name":"Viterbi decoder","score":0.4253947138786316},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3877188563346863},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18873527646064758},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.13309070467948914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1247304379940033},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.07601311802864075}],"concepts":[{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.900291383266449},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6515369415283203},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5969277024269104},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5413960218429565},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5376424193382263},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49939918518066406},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.49066293239593506},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4890356957912445},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.48232099413871765},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4648778438568115},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.46320095658302307},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.45924240350723267},{"id":"https://openalex.org/C2983497884","wikidata":"https://www.wikidata.org/wiki/Q176452","display_name":"Finite state","level":3,"score":0.45013538002967834},{"id":"https://openalex.org/C196455857","wikidata":"https://www.wikidata.org/wiki/Q5473264","display_name":"Forward algorithm","level":5,"score":0.44926732778549194},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4411775469779968},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.426461786031723},{"id":"https://openalex.org/C117379686","wikidata":"https://www.wikidata.org/wiki/Q6996459","display_name":"Viterbi decoder","level":3,"score":0.4253947138786316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3877188563346863},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18873527646064758},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.13309070467948914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1247304379940033},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.07601311802864075},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2011.2132550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2011.2132550","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1493951357","https://openalex.org/W1508165687","https://openalex.org/W1883186006","https://openalex.org/W1969306513","https://openalex.org/W2003333103","https://openalex.org/W2009570821","https://openalex.org/W2016813284","https://openalex.org/W2030634633","https://openalex.org/W2059120410","https://openalex.org/W2068210056","https://openalex.org/W2087284982","https://openalex.org/W2098390086","https://openalex.org/W2100464897","https://openalex.org/W2125838338","https://openalex.org/W2131119226","https://openalex.org/W2137055005","https://openalex.org/W2141216118","https://openalex.org/W2142384583","https://openalex.org/W2151443911","https://openalex.org/W2162415632","https://openalex.org/W2505975651","https://openalex.org/W3104134717","https://openalex.org/W3106123800","https://openalex.org/W3148186152","https://openalex.org/W4245668478","https://openalex.org/W4250389103","https://openalex.org/W4294350219"],"related_works":["https://openalex.org/W2102309991","https://openalex.org/W2062804535","https://openalex.org/W1795315578","https://openalex.org/W2373954783","https://openalex.org/W2143297499","https://openalex.org/W2073817053","https://openalex.org/W4302561434","https://openalex.org/W4294690686","https://openalex.org/W2127464923","https://openalex.org/W1969401149"],"abstract_inverted_index":{"In":[0],"a":[1,12,31,55,93,100,115],"number":[2,57,106],"of":[3,41,58,90,92,107,117,123,132],"applications,":[4],"the":[5,63,72,88,105,138],"underlying":[6],"stochastic":[7],"process":[8,103],"is":[9,23,35,60,67,135],"modeled":[10],"as":[11,71,104],"finite-state":[13],"discrete-time":[14],"Markov":[15,44],"chain":[16],"that":[17,84],"cannot":[18],"be":[19],"observed":[20],"directly":[21],"and":[22,66,126],"represented":[24],"by":[25,62],"an":[26],"auxiliary":[27],"process.":[28],"The":[29,49,130],"maximum":[30],"posteriori":[32],"(MAP)":[33],"estimator":[34,52],"widely":[36],"used":[37],"to":[38,70,99,136],"estimate":[39],"states":[40,125],"this":[42,133],"hidden":[43,124],"model":[45],"through":[46],"available":[47],"observations.":[48],"MAP":[50],"path":[51],"based":[53],"on":[54],"finite":[56,127],"observations":[59,108],"calculated":[61],"Viterbi":[64,73,128],"algorithm,":[65],"often":[68],"referred":[69],"path.":[74],"It":[75],"was":[76],"recently":[77],"shown":[78],"in,":[79],"and,":[80],"(see":[81],"also":[82],"and)":[83],"under":[85],"mild":[86],"conditions,":[87],"sequence":[89],"estimators":[91],"given":[94],"state":[95],"converges":[96],"almost":[97],"surely":[98],"limiting":[101],"regenerative":[102],"approaches":[109],"infinity.":[110],"This":[111],"in":[112],"particular":[113],"implies":[114],"law":[116],"large":[118,140],"numbers":[119],"for":[120],"some":[121],"functionals":[122],"paths.":[129],"aim":[131],"paper":[134],"provide":[137],"corresponding":[139],"deviation":[141],"estimates.":[142]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
