{"id":"https://openalex.org/W1982054392","doi":"https://doi.org/10.1109/isit.2014.6875285","title":"Compression and predictive distributions for large alphabet i.i.d and Markov models","display_name":"Compression and predictive distributions for large alphabet i.i.d and Markov models","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W1982054392","doi":"https://doi.org/10.1109/isit.2014.6875285","mag":"1982054392"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2014.6875285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2014.6875285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Information Theory","raw_type":"proceedings-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/A5101438908","display_name":"Xiao Yang","orcid":"https://orcid.org/0000-0001-7992-8546"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiao Yang","raw_affiliation_strings":["Department of Statistics, Yale University, New Haven, CT","Dept. of Stat., Yale Univ., New Haven, CT, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Yale University, New Haven, CT","institution_ids":["https://openalex.org/I32971472"]},{"raw_affiliation_string":"Dept. of Stat., Yale Univ., New Haven, CT, USA#TAB#","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058660064","display_name":"Andrew R. Barron","orcid":"https://orcid.org/0000-0002-2018-8288"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew R. Barron","raw_affiliation_strings":["Department of Statistics, Yale University, New Haven, CT","Dept. of Stat., Yale Univ., New Haven, CT, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Yale University, New Haven, CT","institution_ids":["https://openalex.org/I32971472"]},{"raw_affiliation_string":"Dept. of Stat., Yale Univ., New Haven, CT, USA#TAB#","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101438908"],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":null,"apc_paid":null,"fwci":0.409,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72583022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"23","issue":null,"first_page":"2504","last_page":"2508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":1.0,"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/T11269","display_name":"Algorithms and Data Compression","score":1.0,"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":0.9871000051498413,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.982699990272522,"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/poisson-distribution","display_name":"Poisson distribution","score":0.6636878848075867},{"id":"https://openalex.org/keywords/alphabet","display_name":"Alphabet","score":0.6439767479896545},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6377209424972534},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6151727437973022},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5457581281661987},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5241906046867371},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4793342053890228},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4638151526451111},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.44995951652526855},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.44734877347946167},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.43694815039634705},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.4279770255088806},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.41668978333473206},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38834208250045776},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3224692940711975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27241697907447815},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24514728784561157},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21064433455467224},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1321220099925995}],"concepts":[{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.6636878848075867},{"id":"https://openalex.org/C112876837","wikidata":"https://www.wikidata.org/wiki/Q837518","display_name":"Alphabet","level":2,"score":0.6439767479896545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6377209424972534},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6151727437973022},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5457581281661987},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5241906046867371},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4793342053890228},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4638151526451111},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.44995951652526855},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.44734877347946167},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.43694815039634705},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4279770255088806},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.41668978333473206},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38834208250045776},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3224692940711975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27241697907447815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24514728784561157},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21064433455467224},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1321220099925995},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2014.6875285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2014.6875285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309036","display_name":"Purdue University","ror":"https://ror.org/02dqehb95"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1971161599","https://openalex.org/W2010584937","https://openalex.org/W2078645667","https://openalex.org/W2082967074","https://openalex.org/W2114874848","https://openalex.org/W2117959102","https://openalex.org/W2123744935","https://openalex.org/W2133713200","https://openalex.org/W2160709761","https://openalex.org/W2163294786","https://openalex.org/W2751862591","https://openalex.org/W3099411104","https://openalex.org/W4230818032"],"related_works":["https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W2194396582","https://openalex.org/W2082284720","https://openalex.org/W2116722627","https://openalex.org/W2537260108","https://openalex.org/W2379938888","https://openalex.org/W4233405330","https://openalex.org/W2792905593","https://openalex.org/W2012669748"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"coding":[3,25],"and":[4,21,47,87],"predicting":[5],"sequences":[6],"of":[7,31,63,89,100],"random":[8],"variables":[9],"generated":[10],"from":[11,17],"a":[12,23,29,71,98,108],"large":[13],"alphabet.":[14],"We":[15],"start":[16],"the":[18,61,67,77,84,94,120],"i.i.d":[19,121],"model":[20],"propose":[22],"simple":[24],"distribution":[26],"formulated":[27],"by":[28],"product":[30,99],"tilted":[32,101],"Poisson":[33,102],"distributions":[34],"which":[35,74],"achieves":[36],"close":[37],"to":[38,44,60,119],"optimal":[39],"performance.":[40],"Then":[41],"we":[42],"extend":[43],"Markov":[45],"models,":[46],"in":[48,66,80,114],"particular,":[49],"tree":[50,54],"sources.":[51],"A":[52],"context":[53],"based":[55],"algorithm":[56,73],"is":[57,70,116],"designed":[58],"according":[59],"frequency":[62],"various":[64],"contexts":[65,95],"data.":[68],"It":[69],"greedy":[72],"seeks":[75],"for":[76],"greatest":[78],"savings":[79,113],"codelength":[81,115],"when":[82],"constructing":[83],"tree.":[85],"Compression":[86],"prediction":[88],"individual":[90],"counts":[91],"associated":[92],"with":[93],"again":[96],"uses":[97],"distributions.":[103],"Implementing":[104],"this":[105],"method":[106],"on":[107],"Chinese":[109],"novel,":[110],"about":[111],"20.56%":[112],"achieved":[117],"compared":[118],"model.":[122]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
