{"id":"https://openalex.org/W2055892937","doi":"https://doi.org/10.1137/10080659x","title":"Importance Sampling for a Monte Carlo Matrix Multiplication Algorithm, with Application to Information Retrieval","display_name":"Importance Sampling for a Monte Carlo Matrix Multiplication Algorithm, with Application to Information Retrieval","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W2055892937","doi":"https://doi.org/10.1137/10080659x","mag":"2055892937"},"language":"en","primary_location":{"id":"doi:10.1137/10080659x","is_oa":false,"landing_page_url":"https://doi.org/10.1137/10080659x","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"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 Scientific Computing","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/A5057207245","display_name":"Sylvester Eriksson\u2010Bique","orcid":"https://orcid.org/0000-0002-1919-6475"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sylvester Eriksson-Bique","raw_affiliation_strings":["sylvester.eriksson-bique@helsinki.fi#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"sylvester.eriksson-bique@helsinki.fi#TAB#","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045925441","display_name":"Mary Solbrig","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mary Solbrig","raw_affiliation_strings":["solbrigm@reed.edu#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"solbrigm@reed.edu#TAB#","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110107525","display_name":"Michael Stefanelli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Stefanelli","raw_affiliation_strings":["stefane3@tcnj.edu#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"stefane3@tcnj.edu#TAB#","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028751580","display_name":"Sarah Warkentin","orcid":"https://orcid.org/0000-0002-6678-5256"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarah Warkentin","raw_affiliation_strings":["swarkentin@hmc.edu#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"swarkentin@hmc.edu#TAB#","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040189103","display_name":"Ralph Abbey","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ralph Abbey","raw_affiliation_strings":["rwabbey@ncsu.edu and ipsen@math.ncsu.edu#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"rwabbey@ncsu.edu and ipsen@math.ncsu.edu#TAB#","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036959652","display_name":"Ilse C. F. Ipsen","orcid":"https://orcid.org/0000-0001-5645-5854"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ilse C. F. Ipsen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6379,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.90635235,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"33","issue":"4","first_page":"1689","last_page":"1706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9998999834060669,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9998999834060669,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6951414346694946},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6461297273635864},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6268730759620667},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6141802072525024},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.5935919880867004},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5383843183517456},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5282846093177795},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.5263189673423767},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4839928150177002},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.4152980446815491},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2805580496788025},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.24562376737594604},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09081083536148071}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6951414346694946},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6461297273635864},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6268730759620667},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6141802072525024},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.5935919880867004},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5383843183517456},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5282846093177795},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.5263189673423767},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4839928150177002},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.4152980446815491},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2805580496788025},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.24562376737594604},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09081083536148071},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/10080659x","is_oa":false,"landing_page_url":"https://doi.org/10.1137/10080659x","pdf_url":null,"source":{"id":"https://openalex.org/S165512578","display_name":"SIAM Journal on Scientific Computing","issn_l":"1064-8275","issn":["1064-8275","1095-7197"],"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 Scientific Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1488441684","https://openalex.org/W1531947739","https://openalex.org/W1587887312","https://openalex.org/W1595409123","https://openalex.org/W1672197616","https://openalex.org/W1964718108","https://openalex.org/W1970576574","https://openalex.org/W1979750072","https://openalex.org/W1982114217","https://openalex.org/W1985269159","https://openalex.org/W1988090537","https://openalex.org/W2012365979","https://openalex.org/W2015731569","https://openalex.org/W2042465463","https://openalex.org/W2062616135","https://openalex.org/W2073067135","https://openalex.org/W2075194837","https://openalex.org/W2077658674","https://openalex.org/W2089497633","https://openalex.org/W2113359929","https://openalex.org/W2117756735","https://openalex.org/W2119885577","https://openalex.org/W2131034613","https://openalex.org/W2152132528","https://openalex.org/W2152828142","https://openalex.org/W2172028873","https://openalex.org/W3143596294"],"related_works":["https://openalex.org/W3099313426","https://openalex.org/W4287593139","https://openalex.org/W752783541","https://openalex.org/W1506547947","https://openalex.org/W4206811032","https://openalex.org/W2995605830","https://openalex.org/W4239424132","https://openalex.org/W2596457687","https://openalex.org/W3212757063","https://openalex.org/W2086123442"],"abstract_inverted_index":{"We":[0,35],"perform":[1],"importance":[2],"sampling":[3],"for":[4],"a":[5],"randomized":[6],"matrix":[7,30],"multiplication":[8],"algorithm":[9],"by":[10],"Drineas,":[11],"Kannan,":[12],"and":[13,15,43,79],"Mahoney":[14],"derive":[16,44],"probabilities":[17,39,42,54,70,78],"that":[18,67,80],"minimize":[19],"the":[20,26,29,33,48,52,68,76],"expected":[21],"value":[22],"(with":[23],"regard":[24],"to":[25],"distributions":[27],"of":[28,32,51],"elements)":[31],"variance.":[34],"compare":[36],"these":[37],"optimized":[38,53,69],"with":[40,59],"uniform":[41,77],"conditions":[45],"under":[46],"which":[47],"actual":[49],"variance":[50],"is":[55],"lower.":[56],"Numerical":[57],"experiments":[58],"query":[60],"matching":[61],"in":[62],"information":[63],"retrieval":[64],"applications":[65],"illustrate":[66],"produce":[71],"more":[72],"accurate":[73],"matchings":[74],"than":[75],"they":[81],"can":[82],"also":[83],"be":[84],"computed":[85],"efficiently.":[86]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
