{"id":"https://openalex.org/W183198974","doi":"https://doi.org/10.1007/978-3-642-31594-7_12","title":"Efficient Sampling Methods for Discrete Distributions","display_name":"Efficient Sampling Methods for Discrete Distributions","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W183198974","doi":"https://doi.org/10.1007/978-3-642-31594-7_12","mag":"183198974"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-642-31594-7_12","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-31594-7_12","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/11858/00-001M-0000-002B-85D0-8","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044394587","display_name":"Karl Bringmann","orcid":"https://orcid.org/0000-0003-1356-5177"},"institutions":[{"id":"https://openalex.org/I4210109712","display_name":"Max Planck Institute for Informatics","ror":"https://ror.org/01w19ak89","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210109712"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Karl Bringmann","raw_affiliation_strings":["Max Planck Institute for Informatics, Campus E1.4, 66123, Saarbr\u00fccken, Germany","Max Planck Institute for informatics, Saarbr\u00fccken, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Informatics, Campus E1.4, 66123, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210109712"]},{"raw_affiliation_string":"Max Planck Institute for informatics, Saarbr\u00fccken, Germany","institution_ids":["https://openalex.org/I4210109712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075970062","display_name":"\u039a\u03c9\u03bd\u03c3\u03c4\u03b1\u03bd\u03c4\u03af\u03bd\u03bf\u03c2 \u03a0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03bf\u03c5","orcid":"https://orcid.org/0000-0002-9258-6082"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Konstantinos Panagiotou","raw_affiliation_strings":["Department of Mathematics, University of Munich, Theresienstra\u00dfe 39, 80333, Munich, Germany","Department of Mathematics, University of Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Munich, Theresienstra\u00dfe 39, 80333, Munich, Germany","institution_ids":[]},{"raw_affiliation_string":"Department of Mathematics, University of Munich, Munich, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044394587"],"corresponding_institution_ids":["https://openalex.org/I4210109712"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":2.9748,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.92160523,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"133","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9998000264167786,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9983999729156494,"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/event","display_name":"Event (particle physics)","score":0.6358104944229126},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.6304445266723633},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5984845161437988},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5971837639808655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5387639999389648},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.5115052461624146},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5054402351379395},{"id":"https://openalex.org/keywords/poisson-sampling","display_name":"Poisson sampling","score":0.45144176483154297},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.44379037618637085},{"id":"https://openalex.org/keywords/rejection-sampling","display_name":"Rejection sampling","score":0.4274842441082001},{"id":"https://openalex.org/keywords/probability-mass-function","display_name":"Probability mass function","score":0.42028772830963135},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4199095070362091},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.411077618598938},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.38272708654403687},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.37997114658355713},{"id":"https://openalex.org/keywords/slice-sampling","display_name":"Slice sampling","score":0.29349350929260254},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23175224661827087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11770132184028625},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.10870930552482605},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.10816696286201477},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.06530684232711792}],"concepts":[{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6358104944229126},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.6304445266723633},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5984845161437988},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5971837639808655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5387639999389648},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.5115052461624146},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5054402351379395},{"id":"https://openalex.org/C82152865","wikidata":"https://www.wikidata.org/wiki/Q7208505","display_name":"Poisson sampling","level":5,"score":0.45144176483154297},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.44379037618637085},{"id":"https://openalex.org/C187192777","wikidata":"https://www.wikidata.org/wiki/Q381699","display_name":"Rejection sampling","level":5,"score":0.4274842441082001},{"id":"https://openalex.org/C197096303","wikidata":"https://www.wikidata.org/wiki/Q869887","display_name":"Probability mass function","level":3,"score":0.42028772830963135},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4199095070362091},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.411077618598938},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.38272708654403687},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.37997114658355713},{"id":"https://openalex.org/C170593435","wikidata":"https://www.wikidata.org/wiki/Q4128565","display_name":"Slice sampling","level":4,"score":0.29349350929260254},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23175224661827087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11770132184028625},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.10870930552482605},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.10816696286201477},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.06530684232711792},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C37669827","wikidata":"https://www.wikidata.org/wiki/Q6904703","display_name":"Monte Carlo molecular modeling","level":4,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/978-3-642-31594-7_12","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-31594-7_12","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:pure.mpg.de:item_2351302","is_oa":true,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-002B-85D0-8","pdf_url":"http://hdl.handle.net/11858/00-001M-0000-002B-85D0-8","source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithmica","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.368.9459","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.368.9459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.mpi-inf.mpg.de/~kbringma/paper/2012ICALP.pdf","raw_type":"text"},{"id":"pmh:oai:pure.mpg.de:item_1858469","is_oa":false,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-0014-BBDB-2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Automata, Languages, and Programming","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:pure.mpg.de:item_2351302","is_oa":true,"landing_page_url":"http://hdl.handle.net/11858/00-001M-0000-002B-85D0-8","pdf_url":"http://hdl.handle.net/11858/00-001M-0000-002B-85D0-8","source":{"id":"https://openalex.org/S4306400654","display_name":"MPG.PuRe (Max Planck Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149899117","host_organization_name":"Max Planck Society","host_organization_lineage":["https://openalex.org/I149899117"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithmica","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W183198974.pdf"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W111167761","https://openalex.org/W170766065","https://openalex.org/W1523494361","https://openalex.org/W1551631489","https://openalex.org/W1580420215","https://openalex.org/W1756477312","https://openalex.org/W1975763279","https://openalex.org/W1981663184","https://openalex.org/W2017952514","https://openalex.org/W2024859348","https://openalex.org/W2068902429","https://openalex.org/W2119885577","https://openalex.org/W2139639963","https://openalex.org/W2152828142","https://openalex.org/W2752853835","https://openalex.org/W2911302472","https://openalex.org/W2996041333","https://openalex.org/W3041834803","https://openalex.org/W3136533148","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3083491872","https://openalex.org/W2066126998","https://openalex.org/W2033057584","https://openalex.org/W4200629989","https://openalex.org/W2122865681","https://openalex.org/W2018632396","https://openalex.org/W1969740448","https://openalex.org/W4293690604","https://openalex.org/W929711691","https://openalex.org/W183198974"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
