{"id":"https://openalex.org/W3117899385","doi":"https://doi.org/10.1109/hpec43674.2020.9286171","title":"Multiscale Data Analysis Using Binning, Tensor Decompositions, and Backtracking","display_name":"Multiscale Data Analysis Using Binning, Tensor Decompositions, and Backtracking","publication_year":2020,"publication_date":"2020-09-22","ids":{"openalex":"https://openalex.org/W3117899385","doi":"https://doi.org/10.1109/hpec43674.2020.9286171","mag":"3117899385"},"language":"en","primary_location":{"id":"doi:10.1109/hpec43674.2020.9286171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec43674.2020.9286171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","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/A5055226258","display_name":"Dimitri Leggas","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dimitri Leggas","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006882381","display_name":"Thomas Henretty","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas S. Henretty","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003537070","display_name":"James Ezick","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Ezick","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104040289","display_name":"Muthu Manikandan Baskaran","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muthu Baskaran","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027791876","display_name":"Brendan von Hofe","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brendan von Hofe","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000105945","display_name":"Grace Cimaszewski","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Grace Cimaszewski","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011836461","display_name":"M. Harper Langston","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Harper Langston","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108503417","display_name":"Richard Lethin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102519","display_name":"Reservoir Labs (United States)","ror":"https://ror.org/01a3m3f05","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102519"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard Lethin","raw_affiliation_strings":["Reservoir Labs, Inc., New York, NY"],"affiliations":[{"raw_affiliation_string":"Reservoir Labs, Inc., New York, NY","institution_ids":["https://openalex.org/I4210102519"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5055226258"],"corresponding_institution_ids":["https://openalex.org/I4210102519"],"apc_list":null,"apc_paid":null,"fwci":0.5638,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60617284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2020","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"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/T11269","display_name":"Algorithms and Data Compression","score":0.9542999863624573,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9474999904632568,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/backtracking","display_name":"Backtracking","score":0.7398615479469299},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6289964318275452},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5762709379196167},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32336342334747314},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28799694776535034},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2769692540168762},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.06974127888679504}],"concepts":[{"id":"https://openalex.org/C156884757","wikidata":"https://www.wikidata.org/wiki/Q798554","display_name":"Backtracking","level":2,"score":0.7398615479469299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6289964318275452},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5762709379196167},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32336342334747314},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28799694776535034},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2769692540168762},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.06974127888679504}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/hpec43674.2020.9286171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec43674.2020.9286171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},{"id":"mag:3163696679","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202102260017612618","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2024165284","https://openalex.org/W2024356620","https://openalex.org/W2482092413","https://openalex.org/W2766476454","https://openalex.org/W2801272135","https://openalex.org/W2914442069","https://openalex.org/W2991149580","https://openalex.org/W3021088942"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2760348722","https://openalex.org/W2783885583","https://openalex.org/W2120095724","https://openalex.org/W2368326437","https://openalex.org/W2357479099","https://openalex.org/W2364309619","https://openalex.org/W2371864976","https://openalex.org/W2391415040"],"abstract_inverted_index":{"Large":[0],"data":[1,18,47,138],"sets":[2],"can":[3],"contain":[4],"patterns":[5,23,100,141],"at":[6,24,38],"multiple":[7,39],"scales":[8,40],"(spatial,":[9],"temporal,":[10],"etc.).":[11],"In":[12,28],"practice,":[13],"it":[14,118],"is":[15,109],"useful":[16],"for":[17],"exploration":[19],"techniques":[20],"to":[21,35,98,111,140],"detect":[22,36],"each":[25],"relevant":[26],"scale.":[27],"this":[29],"paper,":[30],"we":[31,127],"develop":[32,81,128],"an":[33,44],"approach":[34],"activities":[37],"using":[41],"tensor":[42,74,116],"decomposition,":[43],"unsupervised":[45],"high-dimensional":[46],"analysis":[48],"technique":[49,147],"that":[50,63,131],"finds":[51],"correlations":[52],"between":[53],"different":[54,90],"features":[55,95],"in":[56,75,96,143,150,160],"the":[57,64,70,73,121,124,133,144,151],"data.":[58,125,167],"This":[59],"method":[60,83],"typically":[61],"requires":[62],"feature":[65],"values":[66],"are":[67,148],"discretized":[68],"during":[69],"construction":[71],"of":[72,84,93,104,123,135,153],"a":[76,82,102],"process":[77],"called":[78],"\u201cbinning.\u201d":[79],"We":[80],"constructing":[85],"and":[86,155,159],"decomposing":[87],"tensors":[88],"with":[89],"binning":[91,108],"schemes":[92],"various":[94],"order":[97],"uncover":[99],"across":[101],"set":[103],"user-defined":[105],"scales.":[106],"While":[107],"necessary":[110],"obtain":[112],"interpretable":[113],"results":[114],"from":[115],"decompositions,":[117],"also":[119],"decreases":[120],"specificity":[122],"Thus,":[126],"backtracking":[129],"methods":[130],"enable":[132],"recovery":[134],"original":[136],"source":[137],"corresponding":[139],"found":[142],"decomposition.":[145],"These":[146],"discussed":[149],"context":[152],"spatiotemporal":[154],"network":[156],"traffic":[157],"data,":[158],"particular":[161],"on":[162],"Automatic":[163],"Identification":[164],"System":[165],"(AIS)":[166]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
