{"id":"https://openalex.org/W4200201902","doi":"https://doi.org/10.1109/hpec49654.2021.9622828","title":"An All\u2013at\u2013Once CP Decomposition Method for Count Tensors","display_name":"An All\u2013at\u2013Once CP Decomposition Method for Count Tensors","publication_year":2021,"publication_date":"2021-09-20","ids":{"openalex":"https://openalex.org/W4200201902","doi":"https://doi.org/10.1109/hpec49654.2021.9622828"},"language":"en","primary_location":{"id":"doi:10.1109/hpec49654.2021.9622828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec49654.2021.9622828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5049815529","display_name":"Teresa Ranadive","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113003","display_name":"Physical Sciences (United States)","ror":"https://ror.org/021qvjc46","country_code":"US","type":"company","lineage":["https://openalex.org/I4210113003"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Teresa M. Ranadive","raw_affiliation_strings":["Laboratory for Physical Sciences, College Park, MD"],"affiliations":[{"raw_affiliation_string":"Laboratory for Physical Sciences, College Park, MD","institution_ids":["https://openalex.org/I4210113003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104040289","display_name":"Muthu Manikandan Baskaran","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113003","display_name":"Physical Sciences (United States)","ror":"https://ror.org/021qvjc46","country_code":"US","type":"company","lineage":["https://openalex.org/I4210113003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muthu M. Baskaran","raw_affiliation_strings":["Laboratory for Physical Sciences, College Park, MD"],"affiliations":[{"raw_affiliation_string":"Laboratory for Physical Sciences, College Park, MD","institution_ids":["https://openalex.org/I4210113003"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049815529"],"corresponding_institution_ids":["https://openalex.org/I4210113003"],"apc_list":null,"apc_paid":null,"fwci":0.6707,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64570738,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9046000242233276,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.8007155656814575},{"id":"https://openalex.org/keywords/tucker-decomposition","display_name":"Tucker decomposition","score":0.7376272082328796},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6698184013366699},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.6521972417831421},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4904312789440155},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4792768657207489},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43204420804977417},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.1197054386138916}],"concepts":[{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.8007155656814575},{"id":"https://openalex.org/C42704193","wikidata":"https://www.wikidata.org/wiki/Q7851097","display_name":"Tucker decomposition","level":4,"score":0.7376272082328796},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6698184013366699},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.6521972417831421},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4904312789440155},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4792768657207489},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43204420804977417},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.1197054386138916},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpec49654.2021.9622828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec49654.2021.9622828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1870083876","https://openalex.org/W1988720938","https://openalex.org/W2000215628","https://openalex.org/W2024165284","https://openalex.org/W2024356620","https://openalex.org/W2026034143","https://openalex.org/W2043342740","https://openalex.org/W2064321206","https://openalex.org/W2066392792","https://openalex.org/W2129455341","https://openalex.org/W2147215426","https://openalex.org/W2476891002","https://openalex.org/W2541878878","https://openalex.org/W2746170296","https://openalex.org/W2766476454","https://openalex.org/W2766967332","https://openalex.org/W2909892283","https://openalex.org/W2948703217","https://openalex.org/W2949279215","https://openalex.org/W2991149580","https://openalex.org/W2991157588","https://openalex.org/W3005990752","https://openalex.org/W3043975730","https://openalex.org/W3045398543","https://openalex.org/W3091430646","https://openalex.org/W3096024647","https://openalex.org/W3098758500","https://openalex.org/W3103400026","https://openalex.org/W3105254673","https://openalex.org/W3114643644","https://openalex.org/W3158766173","https://openalex.org/W3160314930","https://openalex.org/W4300574628","https://openalex.org/W4301909677","https://openalex.org/W6721826398","https://openalex.org/W6754166619","https://openalex.org/W6781696107","https://openalex.org/W6794547258","https://openalex.org/W6844680021","https://openalex.org/W6958474770"],"related_works":["https://openalex.org/W3151473062","https://openalex.org/W2891735857","https://openalex.org/W3127610061","https://openalex.org/W47805180","https://openalex.org/W2093953080","https://openalex.org/W2891277085","https://openalex.org/W2347172331","https://openalex.org/W4226375746","https://openalex.org/W4379519626","https://openalex.org/W4281643854"],"abstract_inverted_index":{"CANDECOMP/PARAFAC":[0],"(CP)":[1],"tensor":[2,62,113,133],"decomposition":[3,27,67,93,98,114,164],"is":[4,72],"a":[5,117,125],"popular":[6],"method":[7],"for":[8,90,111],"detecting":[9],"latent":[10,167],"behaviors":[11],"in":[12,161],"real\u2013world":[13],"data":[14,17,143],"sets.":[15],"As":[16],"sets":[18,36],"grow":[19],"larger":[20],"and":[21,166],"more":[22,24],"elaborate,":[23],"sophisticated":[25],"CP":[26,92],"algorithms":[28,89,102],"are":[29,148],"required":[30],"to":[31,64,150],"enable":[32],"these":[33],"discoveries.":[34],"Data":[35],"from":[37,60,141],"many":[38,145],"applications":[39],"can":[40],"be":[41],"represented":[42],"as":[43],"count":[44,48,112],"tensors.":[45],"To":[46],"decompose":[47],"tensors,":[49],"one":[50],"should":[51],"minimize":[52],"the":[53,56,75,84,132],"sum":[54],"of":[55,83,129,146,163],"generalized":[57,118],"Kullback\u2013Leibler":[58],"divergences":[59],"each":[61,65],"entry":[63],"corresponding":[66],"entry.":[68],"Most":[69],"often,":[70],"this":[71],"done":[73],"using":[74],"algorithm":[76,110],"CP\u2013APR":[77],"(CP\u2013Alternating":[78],"Poisson":[79],"Regression).":[80],"In":[81],"view":[82],"fact":[85],"that":[86,115,155],"all-at-once":[87],"optimization":[88],"related":[91,149],"problems":[94],"often":[95],"achieve":[96],"better":[97],"accuracy":[99,165],"than":[100],"alternating":[101],"like":[103],"CP\u2013APR,":[104,159],"we":[105,153],"develop":[106],"CP\u2013POPT\u2013GDGN,":[107],"an":[108],"all\u2013at\u2013once":[109],"utilizes":[116],"damped":[119],"Gauss-Newton":[120],"method.":[121],"We":[122],"then":[123],"implement":[124],"highly":[126],"efficient":[127],"version":[128],"CP\u2013POPT\u2013GDGN":[130,156],"into":[131],"package":[134],"ENSIGN.":[135],"After":[136],"decomposing":[137],"several":[138],"tensors":[139],"formed":[140],"real-world":[142],"sets,":[144],"which":[147],"network":[151],"traffic,":[152],"see":[154],"typically":[157],"outperforms":[158],"both":[160],"terms":[162],"behavior":[168],"detection.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}