{"id":"https://openalex.org/W2987949979","doi":"https://doi.org/10.1145/3357384.3358062","title":"Efficient Sequential and Parallel Algorithms for Estimating Higher Order Spectra","display_name":"Efficient Sequential and Parallel Algorithms for Estimating Higher Order Spectra","publication_year":2019,"publication_date":"2019-11-03","ids":{"openalex":"https://openalex.org/W2987949979","doi":"https://doi.org/10.1145/3357384.3358062","mag":"2987949979"},"language":"en","primary_location":{"id":"doi:10.1145/3357384.3358062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3357384.3358062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3357384.3358062","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3357384.3358062","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009344627","display_name":"Zigeng Wang","orcid":"https://orcid.org/0000-0001-5611-2165"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zigeng Wang","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001504077","display_name":"Abdullah-Al Mamun","orcid":null},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]},{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdullah-Al Mamun","raw_affiliation_strings":["University of Connecticut &amp; Google LLC, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"University of Connecticut &amp; Google LLC, Storrs, CT, USA","institution_ids":["https://openalex.org/I1291425158","https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013075695","display_name":"Xingyu Cai","orcid":"https://orcid.org/0000-0003-1537-7161"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingyu Cai","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065854596","display_name":"\u041d\u0430\u043b\u0438\u043d\u0438 \u0420\u0430\u0432\u0438\u0448\u0430\u043d\u043a\u0435\u0440","orcid":"https://orcid.org/0000-0002-2028-4771"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nalini Ravishanker","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034177039","display_name":"Sanguthevar Rajasekaran","orcid":null},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanguthevar Rajasekaran","raw_affiliation_strings":["University of Connecticut, Storrs, CT, USA"],"affiliations":[{"raw_affiliation_string":"University of Connecticut, Storrs, CT, USA","institution_ids":["https://openalex.org/I140172145"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5009344627"],"corresponding_institution_ids":["https://openalex.org/I140172145"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.13311016,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1743","last_page":"1752"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9990000128746033,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9990000128746033,"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/T10320","display_name":"Neural Networks and Applications","score":0.9667999744415283,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trispectrum","display_name":"Trispectrum","score":0.8966791033744812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7956318855285645},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6848887801170349},{"id":"https://openalex.org/keywords/bispectrum","display_name":"Bispectrum","score":0.586035430431366},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5075815916061401},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.4872230589389801},{"id":"https://openalex.org/keywords/parallel-algorithm","display_name":"Parallel algorithm","score":0.4856201708316803},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.47641241550445557},{"id":"https://openalex.org/keywords/cost-efficiency","display_name":"Cost efficiency","score":0.4229559004306793},{"id":"https://openalex.org/keywords/analysis-of-parallel-algorithms","display_name":"Analysis of parallel algorithms","score":0.41547682881355286}],"concepts":[{"id":"https://openalex.org/C2780973409","wikidata":"https://www.wikidata.org/wiki/Q2410583","display_name":"Trispectrum","level":5,"score":0.8966791033744812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7956318855285645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6848887801170349},{"id":"https://openalex.org/C114148568","wikidata":"https://www.wikidata.org/wiki/Q2410583","display_name":"Bispectrum","level":3,"score":0.586035430431366},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5075815916061401},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.4872230589389801},{"id":"https://openalex.org/C120373497","wikidata":"https://www.wikidata.org/wiki/Q1087987","display_name":"Parallel algorithm","level":2,"score":0.4856201708316803},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.47641241550445557},{"id":"https://openalex.org/C11644782","wikidata":"https://www.wikidata.org/wiki/Q15401790","display_name":"Cost efficiency","level":2,"score":0.4229559004306793},{"id":"https://openalex.org/C538114610","wikidata":"https://www.wikidata.org/wiki/Q24282658","display_name":"Analysis of parallel algorithms","level":3,"score":0.41547682881355286},{"id":"https://openalex.org/C152321242","wikidata":"https://www.wikidata.org/wiki/Q7048759","display_name":"Non-Gaussianity","level":4,"score":0.0},{"id":"https://openalex.org/C85725439","wikidata":"https://www.wikidata.org/wiki/Q466686","display_name":"Anisotropy","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.0},{"id":"https://openalex.org/C207297109","wikidata":"https://www.wikidata.org/wiki/Q15605","display_name":"Cosmic microwave background","level":3,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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:10.1145/3357384.3358062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3357384.3358062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3357384.3358062","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3357384.3358062","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3357384.3358062","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3357384.3358062","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1160631943","display_name":null,"funder_award_id":"1447711, 1514357, 1743418, and 1843025","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1198520646","display_name":null,"funder_award_id":"1447711","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4285149376","display_name":null,"funder_award_id":"1743418","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7641761490","display_name":null,"funder_award_id":"1843025","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G783915353","display_name":null,"funder_award_id":"1514357","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2987949979.pdf","grobid_xml":"https://content.openalex.org/works/W2987949979.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1509168122","https://openalex.org/W1850213641","https://openalex.org/W1875312086","https://openalex.org/W2004406940","https://openalex.org/W2023719941","https://openalex.org/W2060814311","https://openalex.org/W2097755092","https://openalex.org/W2120490947","https://openalex.org/W2122914407","https://openalex.org/W2132268306","https://openalex.org/W2138219528","https://openalex.org/W2590366910","https://openalex.org/W2785061010","https://openalex.org/W3100066175","https://openalex.org/W4241574976"],"related_works":["https://openalex.org/W1964915218","https://openalex.org/W2013913072","https://openalex.org/W2114801315","https://openalex.org/W3123992650","https://openalex.org/W2023559230","https://openalex.org/W2162286639","https://openalex.org/W2734655831","https://openalex.org/W1988199062","https://openalex.org/W2008341068","https://openalex.org/W2537880717"],"abstract_inverted_index":{"Higher":[0],"order":[1,46],"spectra":[2,47],"(HOS)":[3],"are":[4,95],"a":[5,49,122,174],"powerful":[6],"tool":[7],"in":[8,22,159],"nonlinear":[9],"time":[10,57,77],"series":[11],"analysis":[12,73],"and":[13,26,37,79,87,127,132,156,162,178,185,193,205,212,226,229],"they":[14],"have":[15,99],"been":[16,100],"extensively":[17],"used":[18],"as":[19,66],"feature":[20],"representations":[21],"data":[23],"mining,":[24],"communications":[25],"cosmology":[27],"domains.":[28],"However,":[29],"HOS":[30,72,94,115,135],"estimation":[31],"suffers":[32],"from":[33],"high":[34],"computational":[35,154,225],"cost":[36,155],"memory":[38,133,157,183,227],"consumption.":[39],"Any":[40],"algorithm":[41],"for":[42,75,92,114,130,202],"computing":[43,93],"the":[44,59,70,152,187,191,194,214],"kth":[45],"on":[48,102,141,190],"dataset":[50],"of":[51,124],"size":[52,61],"n":[53],"needs":[54],"O(n^k-1":[55,64],")":[56,65],"since":[58],"output":[60],"will":[62],"be":[63,139],"well,":[67],"which":[68,137],"makes":[69],"direct":[71,83],"difficult":[74],"long":[76],"series,":[78],"further":[80],"prohibits":[81],"its":[82],"deployment":[84],"to":[85,109,235],"resource-limited":[86],"time-sensitive":[88],"applications.":[89],"Existing":[90],"algorithms":[91,113,129,149,180,201,222,232],"either":[96],"inefficient":[97],"or":[98,145],"implemented":[101],"obsolete":[103],"architectures.":[104],"Thus":[105],"it":[106],"is":[107,240],"essential":[108],"develop":[110],"efficient":[111,134],"generic":[112,125],"estimations.":[116,207],"In":[117],"this":[118],"paper,":[119],"we":[120,172,198],"present":[121,186],"package":[123],"sequential":[126],"parallel":[128,143,188,231],"computationally":[131],"estimations":[136],"can":[138],"employed":[140],"any":[142],"machine":[144],"platform.":[146],"Our":[147],"proposed":[148,215],"largely":[150],"reduce":[151],"HOS'":[153],"usage":[158,184],"spectrum":[160],"multiplication":[161],"smoothing":[163],"steps":[164],"through":[165],"carefully":[166],"designed":[167],"prefix":[168],"sum":[169],"operations.":[170],"Moreover,":[171],"employ":[173],"matrix":[175],"partitioning":[176],"technique":[177],"design":[179],"with":[181],"optimal":[182],"approaches":[189],"PRAM":[192],"mesh":[195],"models.":[196],"Furthermore,":[197],"implement":[199],"our":[200,221,230],"both":[203],"bispectrum":[204],"trispectrum":[206],"We":[208],"conduct":[209],"extensive":[210],"experiments":[211],"cross-compare":[213],"algorithms'":[216],"performance.":[217],"Results":[218],"show":[219],"that":[220],"achieve":[223,233],"state-of-the-art":[224],"efficiency,":[228],"close":[234],"linear":[236],"speedups.":[237],"The":[238],"code":[239],"available":[241],"at":[242],"https://github.com/ZigengWang/HOS.":[243]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
