{"id":"https://openalex.org/W4416513150","doi":"https://doi.org/10.1109/tsp.2025.3632844","title":"Guaranteed Multidimensional Time Series Prediction via Deterministic Tensor Completion Theory","display_name":"Guaranteed Multidimensional Time Series Prediction via Deterministic Tensor Completion Theory","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416513150","doi":"https://doi.org/10.1109/tsp.2025.3632844"},"language":null,"primary_location":{"id":"doi:10.1109/tsp.2025.3632844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2025.3632844","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-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/A5037000621","display_name":"Hao Shu","orcid":"https://orcid.org/0009-0002-6456-7009"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Shu","raw_affiliation_strings":["School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China"],"raw_orcid":"https://orcid.org/0009-0002-6456-7009","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jicheng Li","orcid":"https://orcid.org/0000-0001-5743-8642"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jicheng Li","raw_affiliation_strings":["School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China"],"raw_orcid":"https://orcid.org/0000-0001-5743-8642","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yu Jin","orcid":"https://orcid.org/0009-0004-5143-4308"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Jin","raw_affiliation_strings":["School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China"],"raw_orcid":"https://orcid.org/0009-0004-5143-4308","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hailin Wang","orcid":"https://orcid.org/0000-0002-7797-2719"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hailin Wang","raw_affiliation_strings":["School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China"],"raw_orcid":"https://orcid.org/0000-0002-7797-2719","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x02019;an Jiaotong University, Xi&#x02019;an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University Xi&#x2019;an, Shanxi, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.93,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78164251,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"73","issue":null,"first_page":"4638","last_page":"4653"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9128999710083008,"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":0.9128999710083008,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.05260000005364418,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.0020000000949949026,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6794999837875366},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6168000102043152},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5249999761581421},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4871000051498413},{"id":"https://openalex.org/keywords/multidimensional-systems","display_name":"Multidimensional systems","score":0.4336000084877014},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.29649999737739563}],"concepts":[{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6794999837875366},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6168000102043152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5845999717712402},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4871000051498413},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4794999957084656},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45730000734329224},{"id":"https://openalex.org/C158457486","wikidata":"https://www.wikidata.org/wiki/Q17104301","display_name":"Multidimensional systems","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.321399986743927},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29179999232292175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2863999903202057},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2806999981403351},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2025.3632844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2025.3632844","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5989932864","display_name":null,"funder_award_id":"12171384","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1864134408","https://openalex.org/W1925915230","https://openalex.org/W2000015923","https://openalex.org/W2024165284","https://openalex.org/W2031327377","https://openalex.org/W2043571470","https://openalex.org/W2091449379","https://openalex.org/W2115744225","https://openalex.org/W2134332047","https://openalex.org/W2153303375","https://openalex.org/W2342643507","https://openalex.org/W2525732060","https://openalex.org/W2611328865","https://openalex.org/W2768736333","https://openalex.org/W2775387120","https://openalex.org/W2785436244","https://openalex.org/W2803140164","https://openalex.org/W2806382623","https://openalex.org/W2895043543","https://openalex.org/W2902048196","https://openalex.org/W2950126918","https://openalex.org/W2962915592","https://openalex.org/W2963328634","https://openalex.org/W2963529234","https://openalex.org/W2963728452","https://openalex.org/W2963885538","https://openalex.org/W2964006653","https://openalex.org/W2965565138","https://openalex.org/W2971098996","https://openalex.org/W2971507477","https://openalex.org/W2980537499","https://openalex.org/W2989504803","https://openalex.org/W2997857369","https://openalex.org/W3010725993","https://openalex.org/W3080832086","https://openalex.org/W3081388776","https://openalex.org/W3094257649","https://openalex.org/W3107841493","https://openalex.org/W3109157652","https://openalex.org/W3129086483","https://openalex.org/W3131696680","https://openalex.org/W3157507404","https://openalex.org/W3167202680","https://openalex.org/W3179935684","https://openalex.org/W3198546568","https://openalex.org/W3198865231","https://openalex.org/W3204668058","https://openalex.org/W4225816429","https://openalex.org/W4292363360","https://openalex.org/W4294690695","https://openalex.org/W4322704133","https://openalex.org/W4323022420","https://openalex.org/W4353004250","https://openalex.org/W4383890128","https://openalex.org/W4388357039","https://openalex.org/W4400071817","https://openalex.org/W4400524914"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,30,55,119,131,136,141,148],"prediction":[4,20,96,161],"of":[5,33,57],"multidimensional":[6,85,93,132],"time":[7,94,133],"series":[8,95,134],"data":[9],"has":[10],"become":[11],"increasingly":[12],"important":[13],"due":[14],"to":[15,28,50,167],"its":[16],"wide-ranging":[17],"applications.":[18],"Tensor-based":[19],"methods":[21,66,169],"have":[22,47],"gained":[23],"attention":[24],"for":[25,152],"their":[26,73],"ability":[27],"preserve":[29],"inherent":[31],"structure":[32],"such":[34,39],"data.":[35,86,182],"However,":[36],"existing":[37,168],"approaches,":[38],"as":[40,97],"tensor":[41,44,100,114,142],"autoregression":[42],"and":[43,79,103,117,139,163,179],"decomposition,":[45],"often":[46],"consistently":[48],"failed":[49],"provide":[51],"clear":[52],"assertions":[53],"regarding":[54],"number":[56],"samples":[58],"that":[59],"can":[60],"be":[61],"exactly":[62],"predicted.":[63],"While":[64],"matrix-based":[65],"using":[67],"nuclear":[68,143],"norms":[69],"address":[70],"this":[71],"limitation,":[72],"reliance":[74],"on":[75],"matrices":[76],"limits":[77],"accuracy":[78,162],"increases":[80],"computational":[81,164],"costs":[82],"when":[83],"handling":[84],"To":[87],"overcome":[88],"these":[89],"challenges,":[90],"we":[91,110],"reformulate":[92],"a":[98,105,112],"deterministic":[99,113],"completion":[101,115],"problem":[102],"propose":[104],"novel":[106],"theoretical":[107],"framework.":[108],"Specifically,":[109],"develop":[111],"theory":[116],"introduce":[118],"<italic":[120],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[121,190],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Temporal":[122],"Convolutional":[123],"Tensor":[124],"Nuclear":[125],"Norm</i>":[126],"(TCTNN)":[127],"model.":[128],"By":[129],"convolving":[130],"along":[135],"temporal":[137],"dimension":[138],"applying":[140],"norm,":[144],"our":[145],"approach":[146],"identifies":[147],"maximum":[149],"forecast":[150],"horizon":[151],"exact":[153],"predictions.":[154],"Additionally,":[155],"TCTNN":[156],"achieves":[157],"superior":[158],"performance":[159],"in":[160],"efficiency":[165],"compared":[166],"across":[170],"diverse":[171],"real-world":[172],"datasets,":[173],"including":[174],"climate":[175],"temperature,":[176],"network":[177],"flow,":[178],"traffic":[180],"ride":[181],"Our":[183],"implementation":[184],"is":[185],"publicly":[186],"available":[187],"at":[188],"<uri":[189],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/HaoShu2000/TCTNN</uri>.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-16T23:43:54.943958","created_date":"2025-11-23T00:00:00"}
