{"id":"https://openalex.org/W3210340672","doi":"https://doi.org/10.1145/3650030","title":"Better Sum Estimation via Weighted Sampling","display_name":"Better Sum Estimation via Weighted Sampling","publication_year":2024,"publication_date":"2024-03-30","ids":{"openalex":"https://openalex.org/W3210340672","doi":"https://doi.org/10.1145/3650030","mag":"3210340672"},"language":"en","primary_location":{"id":"doi:10.1145/3650030","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3650030","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3650030","source":{"id":"https://openalex.org/S137348503","display_name":"ACM Transactions on Algorithms","issn_l":"1549-6325","issn":["1549-6325","1549-6333"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3650030","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006650132","display_name":"Lorenzo Beretta","orcid":"https://orcid.org/0000-0002-4676-9777"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Lorenzo Beretta","raw_affiliation_strings":["University of Copenhagen, Kobenhavn, Denmark","University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-4676-9777","affiliations":[{"raw_affiliation_string":"University of Copenhagen, Kobenhavn, Denmark","institution_ids":["https://openalex.org/I124055696"]},{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077723390","display_name":"Jakub T\u011btek","orcid":"https://orcid.org/0000-0002-2046-1627"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]},{"id":"https://openalex.org/I83467386","display_name":"IT University of Copenhagen","ror":"https://ror.org/02309jg23","country_code":"DK","type":"education","lineage":["https://openalex.org/I83467386"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jakub T\u011btek","raw_affiliation_strings":["University of Copenhagen, Kobenhavn Denmark","University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-2046-1627","affiliations":[{"raw_affiliation_string":"University of Copenhagen, Kobenhavn Denmark","institution_ids":["https://openalex.org/I83467386","https://openalex.org/I124055696"]},{"raw_affiliation_string":"University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006650132"],"corresponding_institution_ids":["https://openalex.org/I124055696"],"apc_list":null,"apc_paid":null,"fwci":0.6536,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66700979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"20","issue":"3","first_page":"1","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9904000163078308,"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"}},"topics":[{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9904000163078308,"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"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.96670001745224,"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/T11106","display_name":"Data Management and Algorithms","score":0.9387999773025513,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5764288306236267},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5531356930732727},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5430407524108887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4886989891529083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4440990388393402},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.11520683765411377}],"concepts":[{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5764288306236267},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5531356930732727},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5430407524108887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4886989891529083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4440990388393402},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.11520683765411377},{"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3650030","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3650030","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3650030","source":{"id":"https://openalex.org/S137348503","display_name":"ACM Transactions on Algorithms","issn_l":"1549-6325","issn":["1549-6325","1549-6333"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/977a08f9-4168-4998-9179-05be22e54227","is_oa":true,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/977a08f9-4168-4998-9179-05be22e54227","pdf_url":"https://researchprofiles.ku.dk/files/412796304/Better_Sum_Estimation_via_Weighted_Sampling.pdf","source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"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":"Beretta , L & T\u00eatek , J 2024 , ' Better Sum Estimation via Weighted Sampling ' , ACM Transactions on Algorithms , vol. 20 , no. 3 , 27 . https://doi.org/10.1145/3650030","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1145/3650030","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3650030","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3650030","source":{"id":"https://openalex.org/S137348503","display_name":"ACM Transactions on Algorithms","issn_l":"1549-6325","issn":["1549-6325","1549-6333"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2028424385","display_name":null,"funder_award_id":"801199","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4422840520","display_name":null,"funder_award_id":"16582","funder_id":"https://openalex.org/F4320310490","funder_display_name":"Villum Fonden"},{"id":"https://openalex.org/G7842005466","display_name":null,"funder_award_id":"Horizon 2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320310490","display_name":"Villum Fonden","ror":"https://ror.org/007ww2d15"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320334966","display_name":"Bhabha Atomic Research Centre","ror":"https://ror.org/05w6wfp17"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3210340672.pdf","grobid_xml":"https://content.openalex.org/works/W3210340672.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1557882449","https://openalex.org/W1577085959","https://openalex.org/W1593323337","https://openalex.org/W2000154402","https://openalex.org/W2001947543","https://openalex.org/W2007168590","https://openalex.org/W2075709248","https://openalex.org/W2132913310","https://openalex.org/W2148292883","https://openalex.org/W2586277680","https://openalex.org/W2798303859","https://openalex.org/W2962774460","https://openalex.org/W2963568509","https://openalex.org/W3021019285","https://openalex.org/W3037097738","https://openalex.org/W3178525333","https://openalex.org/W3180908601","https://openalex.org/W4233471163","https://openalex.org/W4281744245","https://openalex.org/W4312229003"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2142036596","https://openalex.org/W3107697994"],"abstract_inverted_index":{"Given":[0],"a":[1,8,15,289,304,337,357,373,446,471,530],"large":[2,265,374],"set":[3,57,418],"U":[4,10,43,58,73,419],"where":[5,396,517,543],"each":[6],"item":[7],"\u2208":[9],"has":[11,145],"weight":[12,23],"w":[13],"(":[14,77],"),":[16],"we":[17,47,66,92,103,118,189,229,244,287,319,397,417,458,478,544],"want":[18,48],"to":[19,28,49,69,83,110,202,236,250,281,412,425,428,435],"estimate":[20],"the":[21,55,61,89,100,115,140,226,241,271,282,300,309,316,322,329,332,341,350,366,382,393,423,429,520,524,541],"total":[22],"\\(W=\\sum":[24],"_{a∈":[25],"U}":[26],"w(a)\\)":[27],"within":[29],"factor":[30],"of":[31,168,177,184,210,331,368,384,452,500,508,533],"1\u00b1":[32],"\u025b":[33,221],"with":[34,107,218,492],"some":[35],"constant":[36,203,266,531],"probability":[37],">":[38],"1/2.":[39],"Since":[40],"n":[41,78,169,178,212,277,294],"=|":[42],"|":[44,388,509,511],"is":[45,81,278,336,353,519,560],"large,":[46],"do":[50,262],"this":[51,94,187,285,347,556],"without":[52,326],"looking":[53],"at":[54,455,528],"entire":[56],".":[59,170,239,254,409,497,553],"In":[60,156,186,225,240,284],"traditional":[62],"setting":[63,102,117,144,352,542],"in":[64,96,99,114,131,139,166,175,182,205,208,275,315,340,349,365,540],"which":[65,276],"are":[67,173,199,257,535],"allowed":[68],"sample":[70,105,120,399,461,480,546],"elements":[71],"from":[72,401,404,463,482,548],"uniformly,":[74],"sampling":[75,432,436,440],"\u03a9":[76],")":[79,380,564],"items":[80,106],"necessary":[82],"provide":[84],"any":[85],"non-trivial":[86],"guarantee":[87],"on":[88,220],"estimate.":[90],"Therefore,":[91],"investigate":[93,270],"problem":[95],"different":[97],"settings:":[98],"proportional":[101,109,141,227,301,317],"can":[104,119,398,441,459,545],"probabilities":[108],"their":[111,157,192,231],"weights,":[112],"and":[113,123,134,142,152,163,194,213,261,303,381,407,422,449,484,551],"hybrid":[116,143,242,310,342,351],"both":[121,161,191,206,211,405,481,549],"proportionally":[122],"uniformly.":[124,438],"These":[125],"settings":[126,395],"have":[127,264,363],"applications,":[128],"for":[129,299,308,324,565],"example,":[130],"sublinear-time":[132,369],"algorithms":[133,256,362],"distribution":[135],"testing.":[136],"Sum":[137],"estimation":[138,414],"been":[146],"considered":[147],"before":[148],"by":[149,355,444],"Motwani,":[150],"Panigrahy,":[151],"Xu":[153],"[ICALP,":[154],"2007].":[155],"article,":[158,188],"they":[159],"give":[160,470],"upper":[162,193],"lower":[164,195,216,359],"bounds":[165,172,198,217],"terms":[167,176,183,209],"Their":[171],"near-matching":[174],",":[179,465,486],"but":[180],"not":[181,263,279],"\u025b.":[185,214],"improve":[190,230,245],"bounds.":[196],"Our":[197,255,361],"matching":[200,358],"up":[201],"factors":[204],"settings,":[207],"No":[215],"dependency":[219],"were":[222],"known":[223,280],"previously.":[224],"setting,":[228,243,302,318],"\\(\\tilde{O}(\\sqrt":[232,246],"{n}/ɛ":[233,291],"^{7/2})\\)":[234],"algorithm":[235,298,307,491],"\\(O(\\sqrt":[237,251,290,305,472,494],"{n}/ɛ)\\)":[238,306],"[3]{n}/":[247],"ɛ":[248,296],"^{9/2})\\)":[249],"[3]{n}/ɛ":[252],"^{4/3})\\)":[253,496],"also":[258],"significantly":[259],"simpler":[260],"factors.":[267],"We":[268,344,391,554],"then":[269,433,466],"previously":[272],"unexplored":[273],"scenario":[274],"algorithm.":[283,476],"case,":[286],"obtain":[288],"+":[292],"\\log":[293],"/":[295,474],"^2)\\)":[297,514],"setting.":[311,343],"This":[312,410,537],"means":[313],"that":[314,346,527],"may":[320,479],"remove":[321],"need":[323],"advice":[325],"greatly":[327],"increasing":[328],"complexity":[330,493],"problem,":[333],"while":[334],"there":[335],"major":[338],"difference":[339,348],"prove":[345],"necessary,":[354],"showing":[356],"bound.":[360],"applications":[364],"area":[367],"graph":[370,375],"algorithms.":[371],"Consider":[372],"G":[376],"=(":[377],"V,":[378],"E":[379,389,402,406,464,483,510,552],"task":[383],"(1":[385,505],"\u00b1":[386,506],"\u025b)-approximating":[387],"|.":[390],"consider":[392],"(standard)":[394],"uniformly":[400,462,547],"or":[403],"V":[408,421,485,550],"relates":[411],"sum":[413],"as":[415],"follows:":[416],"=":[420],"weights":[424],"be":[426,442],"equal":[427],"degrees.":[430],"Uniform":[431],"corresponds":[434],"vertices":[437,534],"Proportional":[439],"simulated":[443],"taking":[445],"random":[447],"edge":[448],"picking":[450],"one":[451,499],"its":[453],"endpoints":[454],"random.":[456],"If":[457],"only":[460],"our":[467,487,501],"results":[468,488],"immediately":[469],"{|V|}":[473],"ɛ)\\)":[475],"When":[477],"imply":[489],"an":[490,504],"[3]{|V|}/ɛ":[495],"Surprisingly,":[498],"subroutines":[502],"provides":[503],"\u025b)-approximation":[507],"using":[512],"\\(\\tilde{O}(d/ɛ":[513],"expected":[515],"samples,":[516],"d":[518],"average":[521],"degree,":[522],"under":[523],"mild":[525],"assumption":[526],"least":[529],"fraction":[532],"non-isolated.":[536],"subroutine":[538],"works":[539],"find":[555],"remarkable":[557],"since":[558],"it":[559],"O":[561],"(1/\u025b":[562],"2":[563],"sparse":[566],"graphs.":[567]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-12T08:28:47.272897","created_date":"2025-10-10T00:00:00"}