{"id":"https://openalex.org/W2104279066","doi":"https://doi.org/10.1137/s0895479894262534","title":"A Block-GTH Algorithm for Finding the Stationary Vector of a Markov Chain","display_name":"A Block-GTH Algorithm for Finding the Stationary Vector of a Markov Chain","publication_year":1996,"publication_date":"1996-07-01","ids":{"openalex":"https://openalex.org/W2104279066","doi":"https://doi.org/10.1137/s0895479894262534","mag":"2104279066"},"language":"en","primary_location":{"id":"doi:10.1137/s0895479894262534","is_oa":false,"landing_page_url":"https://doi.org/10.1137/s0895479894262534","pdf_url":null,"source":{"id":"https://openalex.org/S16958353","display_name":"SIAM Journal on Matrix Analysis and Applications","issn_l":"0895-4798","issn":["0895-4798","1095-7162"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Matrix Analysis and Applications","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/A5062480442","display_name":"Dianne P. O\u2019Leary","orcid":"https://orcid.org/0000-0001-9809-5180"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dianne P. O\u2019Leary","raw_affiliation_strings":["University of Maryland, College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029595088","display_name":"Yuan-Jye Jason Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan-Jye Jason Wu","raw_affiliation_strings":["University of Maryland, College Park"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062480442"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":0.5693,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77567713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"17","issue":"3","first_page":"470","last_page":"488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9918000102043152,"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":0.9918000102043152,"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/T12029","display_name":"DNA and Biological Computing","score":0.9812999963760376,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/markov-chain","display_name":"Markov chain","score":0.7765669822692871},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6501701474189758},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6392180323600769},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5820730328559875},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.5155496597290039},{"id":"https://openalex.org/keywords/chain","display_name":"Chain (unit)","score":0.46513527631759644},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.45741647481918335},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.24272361397743225},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06835702061653137}],"concepts":[{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.7765669822692871},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6501701474189758},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6392180323600769},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5820730328559875},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.5155496597290039},{"id":"https://openalex.org/C199185054","wikidata":"https://www.wikidata.org/wiki/Q552299","display_name":"Chain (unit)","level":2,"score":0.46513527631759644},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.45741647481918335},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.24272361397743225},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06835702061653137},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1137/s0895479894262534","is_oa":false,"landing_page_url":"https://doi.org/10.1137/s0895479894262534","pdf_url":null,"source":{"id":"https://openalex.org/S16958353","display_name":"SIAM Journal on Matrix Analysis and Applications","issn_l":"0895-4798","issn":["0895-4798","1095-7162"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Matrix Analysis and Applications","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.307.585","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.307.585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://www.cs.umd.edu/users/oleary/reprints/j42.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1988914905","https://openalex.org/W2061397794","https://openalex.org/W2135622428","https://openalex.org/W2142518629","https://openalex.org/W2519427475"],"related_works":["https://openalex.org/W2357256365","https://openalex.org/W2348502264","https://openalex.org/W2365486383","https://openalex.org/W2362059367","https://openalex.org/W2901443725","https://openalex.org/W2350084742","https://openalex.org/W1660242800","https://openalex.org/W2357988862","https://openalex.org/W1855558850","https://openalex.org/W2077211377"],"abstract_inverted_index":{"Grassman,":[0],"Taksar,":[1],"and":[2,62,84],"Heyman":[3],"have":[4],"proposed":[5],"an":[6,32],"algorithm":[7,30,80],"for":[8],"computing":[9],"the":[10,21,28,35,54,76,79],"stationary":[11,36],"vector":[12,37,69,82],"of":[13,23,53,78],"a":[14,50,68],"Markov":[15],"chain.":[16],"Analysis":[17],"by":[18],"O\u2019Cinneide":[19],"confirmed":[20],"results":[22],"numerical":[24],"experiments,":[25],"proving":[26],"that":[27,64],"GTH":[29,55],"computes":[31],"approximation":[33],"to":[34],"with":[38,70,87],"low":[39,71],"relative":[40,72],"error":[41],"in":[42],"each":[43],"component.":[44],"In":[45],"this":[46],"work,":[47],"we":[48],"develop":[49],"block":[51],"form":[52],"algorithm,":[56],"more":[57],"efficient":[58],"on":[59,81,85],"high-performance":[60],"architectures,":[61],"show":[63],"it":[65],"too":[66],"produces":[67],"error.":[73],"We":[74],"demonstrate":[75],"efficiency":[77],"processors":[83],"workstations":[86],"hierarchical":[88],"memory.":[89]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
