{"id":"https://openalex.org/W2948827545","doi":"https://doi.org/10.1145/3299869.3319854","title":"MNC","display_name":"MNC","publication_year":2019,"publication_date":"2019-06-18","ids":{"openalex":"https://openalex.org/W2948827545","doi":"https://doi.org/10.1145/3299869.3319854","mag":"2948827545"},"language":"en","primary_location":{"id":"doi:10.1145/3299869.3319854","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3299869.3319854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Management of Data","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/A5088692787","display_name":"Johanna Sommer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095996","display_name":"IBM (Germany)","ror":"https://ror.org/00pm7rm97","country_code":"DE","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210095996"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Johanna Sommer","raw_affiliation_strings":["IBM Germany, Ehningen, Germany"],"affiliations":[{"raw_affiliation_string":"IBM Germany, Ehningen, Germany","institution_ids":["https://openalex.org/I4210095996"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053153176","display_name":"Matthias B\u00f6ehm","orcid":"https://orcid.org/0000-0003-1344-3663"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Matthias Boehm","raw_affiliation_strings":["Graz University of Technology, Graz, Austria"],"affiliations":[{"raw_affiliation_string":"Graz University of Technology, Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091709795","display_name":"Alexandre Evfimievski","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexandre V. Evfimievski","raw_affiliation_strings":["IBM Research -- Almaden, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research -- Almaden, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036119025","display_name":"Berthold Reinwald","orcid":null},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Berthold Reinwald","raw_affiliation_strings":["IBM Research -- Almaden, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research -- Almaden, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090729930","display_name":"Peter J. Haas","orcid":"https://orcid.org/0000-0001-5694-3065"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter J. Haas","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088692787"],"corresponding_institution_ids":["https://openalex.org/I4210095996"],"apc_list":null,"apc_paid":null,"fwci":1.476,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.80795715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1607","last_page":"1623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.9970999956130981,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7426505088806152},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.7256324887275696},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.722987711429596},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6763337254524231},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.551123857498169},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.534125566482544},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5004122257232666},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.49442553520202637},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.48515066504478455},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45207101106643677},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45028454065322876},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4468284845352173},{"id":"https://openalex.org/keywords/coefficient-matrix","display_name":"Coefficient matrix","score":0.44441571831703186},{"id":"https://openalex.org/keywords/linear-algebra","display_name":"Linear algebra","score":0.4427035450935364},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.44171959161758423},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3652269244194031},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3334782123565674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.164434552192688},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.11744669079780579}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7426505088806152},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7256324887275696},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722987711429596},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6763337254524231},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.551123857498169},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.534125566482544},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5004122257232666},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.49442553520202637},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.48515066504478455},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45207101106643677},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45028454065322876},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4468284845352173},{"id":"https://openalex.org/C60866291","wikidata":"https://www.wikidata.org/wiki/Q5140577","display_name":"Coefficient matrix","level":3,"score":0.44441571831703186},{"id":"https://openalex.org/C139352143","wikidata":"https://www.wikidata.org/wiki/Q82571","display_name":"Linear algebra","level":2,"score":0.4427035450935364},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.44171959161758423},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3652269244194031},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3334782123565674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.164434552192688},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.11744669079780579},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3299869.3319854","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3299869.3319854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W26556108","https://openalex.org/W31634058","https://openalex.org/W153182319","https://openalex.org/W1557602349","https://openalex.org/W1601435884","https://openalex.org/W1785933978","https://openalex.org/W1832693441","https://openalex.org/W1932742904","https://openalex.org/W1973761208","https://openalex.org/W1979567624","https://openalex.org/W1982092405","https://openalex.org/W1992363839","https://openalex.org/W2007069074","https://openalex.org/W2007259720","https://openalex.org/W2022322548","https://openalex.org/W2022858489","https://openalex.org/W2045938805","https://openalex.org/W2047061289","https://openalex.org/W2058991275","https://openalex.org/W2059696856","https://openalex.org/W2064366207","https://openalex.org/W2073479529","https://openalex.org/W2085140829","https://openalex.org/W2095249664","https://openalex.org/W2103126020","https://openalex.org/W2108614537","https://openalex.org/W2120575449","https://openalex.org/W2139422440","https://openalex.org/W2153160273","https://openalex.org/W2155508779","https://openalex.org/W2160011226","https://openalex.org/W2162277033","https://openalex.org/W2216541755","https://openalex.org/W2293771254","https://openalex.org/W2294501066","https://openalex.org/W2395323716","https://openalex.org/W2402144811","https://openalex.org/W2420293330","https://openalex.org/W2424452828","https://openalex.org/W2508786848","https://openalex.org/W2535724050","https://openalex.org/W2547190417","https://openalex.org/W2569499781","https://openalex.org/W2585098096","https://openalex.org/W2585664214","https://openalex.org/W2612139288","https://openalex.org/W2752885492","https://openalex.org/W2792538726","https://openalex.org/W2798325362","https://openalex.org/W2798839954","https://openalex.org/W2886938735","https://openalex.org/W2899771611","https://openalex.org/W2911324315","https://openalex.org/W2950133940","https://openalex.org/W2950577311","https://openalex.org/W2952219792","https://openalex.org/W2963438348","https://openalex.org/W2963560792","https://openalex.org/W2964054286","https://openalex.org/W3093354955","https://openalex.org/W3098547670","https://openalex.org/W3145128584","https://openalex.org/W4211032723","https://openalex.org/W4242142158","https://openalex.org/W4297971002"],"related_works":["https://openalex.org/W2075142362","https://openalex.org/W2091883426","https://openalex.org/W3173235360","https://openalex.org/W2737338842","https://openalex.org/W2174948646","https://openalex.org/W2357333323","https://openalex.org/W3005946484","https://openalex.org/W2024017047","https://openalex.org/W4318256793","https://openalex.org/W4381050447"],"abstract_inverted_index":{"Efficiently":[0],"computing":[1],"linear":[2,144],"algebra":[3,145],"expressions":[4],"is":[5,88],"central":[6],"to":[7,68,76],"machine":[8],"learning":[9],"(ML)":[10],"systems.":[11,180],"Most":[12],"systems":[13],"support":[14],"sparse":[15,20,48,91],"formats":[16],"and":[17,24,57,62,74,132,139,175],"operations":[18],"because":[19],"matrices":[21,92],"are":[22,53],"ubiquitous":[23],"their":[25],"dense":[26],"representation":[27],"can":[28],"cause":[29],"prohibitive":[30],"overheads.":[31],"Estimating":[32],"the":[33,160],"sparsity":[34,51,134],"of":[35],"intermediates,":[36],"however,":[37],"remains":[38],"a":[39,85,99,118,151],"key":[40,86],"challenge":[41],"when":[42],"generating":[43],"execution":[44],"plans":[45],"or":[46,104],"performing":[47],"operations.":[49],"These":[50],"estimates":[52],"used":[54],"for":[55,129,142],"cost":[56],"memory":[58],"estimates,":[59],"format":[60],"decisions,":[61],"result":[63],"allocation.":[64],"Existing":[65],"estimators":[66,138],"tend":[67],"focus":[69],"on":[70,150],"matrix":[71,122],"products":[72],"only,":[73],"struggle":[75],"attain":[77],"good":[78,164],"accuracy":[79,165],"with":[80,106,166],"low":[81,168],"estimation":[82,153],"overhead.":[83,169],"However,":[84],"observation":[87],"that":[89,124,159],"real-world":[90],"commonly":[93],"exhibit":[94],"structural":[95,127],"properties":[96,128],"such":[97],"as":[98],"single":[100],"non-zero":[101],"per":[102],"row,":[103],"columns":[105],"varying":[107],"sparsity.":[108],"In":[109],"this":[110],"paper,":[111],"we":[112],"introduce":[113],"MNC":[114,161,173],"(Matrix":[115],"Non-zero":[116],"Count),":[117],"remarkably":[119],"simple,":[120],"count-based":[121],"synopsis":[123],"exploits":[125],"these":[126],"efficient,":[130],"accurate,":[131],"general":[133],"estimation.":[135],"We":[136],"describe":[137],"sketch":[140],"propagation":[141],"realistic":[143],"expressions.":[146],"Our":[147],"experiments":[148],"-":[149,157],"new":[152],"benchmark":[154],"called":[155],"SparsEst":[156],"show":[158],"estimator":[162],"yields":[163],"very":[167],"This":[170],"behavior":[171],"makes":[172],"practical":[174],"broadly":[176],"applicable":[177],"in":[178],"ML":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-06-14T00:00:00"}