{"id":"https://openalex.org/W3140640946","doi":"https://doi.org/10.1109/tnnls.2021.3069399","title":"Supervised Learning for Nonsequential Data: A Canonical Polyadic Decomposition Approach","display_name":"Supervised Learning for Nonsequential Data: A Canonical Polyadic Decomposition Approach","publication_year":2021,"publication_date":"2021-04-06","ids":{"openalex":"https://openalex.org/W3140640946","doi":"https://doi.org/10.1109/tnnls.2021.3069399","mag":"3140640946","pmid":"https://pubmed.ncbi.nlm.nih.gov/33822727"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3069399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3069399","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2001.10109","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010477883","display_name":"Alexandros Haliassos","orcid":"https://orcid.org/0000-0001-8856-5193"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Alexandros Haliassos","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College London, London, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070953633","display_name":"Kriton Konstantinidis","orcid":"https://orcid.org/0000-0002-4766-6569"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kriton Konstantinidis","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College London, London, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103001848","display_name":"Danilo P. Mandic","orcid":"https://orcid.org/0000-0001-8432-3963"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Danilo P. Mandic","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Imperial College London, London, U.K","Imperial College London"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Imperial College London","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010477883"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04951691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"10","first_page":"5162","last_page":"5176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"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":0.9998000264167786,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7058301568031311},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6517231464385986},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5760210156440735},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5570774078369141},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4881661534309387},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4768208861351013},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44304826855659485},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43854472041130066},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4309409260749817},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40011948347091675},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37756240367889404},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3596351444721222},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3105451166629791}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7058301568031311},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6517231464385986},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5760210156440735},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5570774078369141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4881661534309387},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4768208861351013},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44304826855659485},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43854472041130066},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4309409260749817},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40011948347091675},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37756240367889404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3596351444721222},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3105451166629791},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tnnls.2021.3069399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3069399","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:33822727","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33822727","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:2001.10109","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.10109","pdf_url":"https://arxiv.org/pdf/2001.10109","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3140640946","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2001.10109.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2001.10109","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2001.10109","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2001.10109","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2001.10109","pdf_url":"https://arxiv.org/pdf/2001.10109","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1246381107","https://openalex.org/W1580176742","https://openalex.org/W1798945469","https://openalex.org/W1802825888","https://openalex.org/W1878057855","https://openalex.org/W1993482030","https://openalex.org/W2000215628","https://openalex.org/W2002485180","https://openalex.org/W2024165284","https://openalex.org/W2025603201","https://openalex.org/W2026698804","https://openalex.org/W2039876715","https://openalex.org/W2088025933","https://openalex.org/W2113055885","https://openalex.org/W2119412403","https://openalex.org/W2121739212","https://openalex.org/W2122816100","https://openalex.org/W2136002544","https://openalex.org/W2140862024","https://openalex.org/W2141200867","https://openalex.org/W2143612262","https://openalex.org/W2163605009","https://openalex.org/W2219888463","https://openalex.org/W2295739661","https://openalex.org/W2295966731","https://openalex.org/W2342432191","https://openalex.org/W2404400936","https://openalex.org/W2431890537","https://openalex.org/W2469230926","https://openalex.org/W2489292218","https://openalex.org/W2505972586","https://openalex.org/W2516041031","https://openalex.org/W2551156993","https://openalex.org/W2617994470","https://openalex.org/W2752217370","https://openalex.org/W2899051391","https://openalex.org/W2920855646","https://openalex.org/W2922105745","https://openalex.org/W2949117887","https://openalex.org/W2951542569","https://openalex.org/W2952655860","https://openalex.org/W2962766718","https://openalex.org/W2962845550","https://openalex.org/W2963638086","https://openalex.org/W2963759574","https://openalex.org/W2964003140","https://openalex.org/W2964121744","https://openalex.org/W2964290417","https://openalex.org/W2970828773","https://openalex.org/W3006217815","https://openalex.org/W3099321628","https://openalex.org/W3099956647","https://openalex.org/W3101570982","https://openalex.org/W3103713775","https://openalex.org/W3121797243","https://openalex.org/W4213251304","https://openalex.org/W4388411486","https://openalex.org/W6631190155","https://openalex.org/W6632540188","https://openalex.org/W6638060716","https://openalex.org/W6638667902","https://openalex.org/W6638868411","https://openalex.org/W6679667936","https://openalex.org/W6681017033","https://openalex.org/W6717575008","https://openalex.org/W6720612731","https://openalex.org/W6724478308","https://openalex.org/W6729942461","https://openalex.org/W6745442365","https://openalex.org/W6759574084","https://openalex.org/W6764213378","https://openalex.org/W6771915822"],"related_works":["https://openalex.org/W3150160418","https://openalex.org/W3199694544","https://openalex.org/W3135564252","https://openalex.org/W3124158795","https://openalex.org/W2591638990","https://openalex.org/W2755299938","https://openalex.org/W3041891788","https://openalex.org/W3006064283","https://openalex.org/W2809174326","https://openalex.org/W2185470268","https://openalex.org/W3120526970","https://openalex.org/W3017178734","https://openalex.org/W2982673118","https://openalex.org/W1854859904","https://openalex.org/W2119352075","https://openalex.org/W3096503561","https://openalex.org/W2894278606","https://openalex.org/W2100380725","https://openalex.org/W2979873887","https://openalex.org/W2906845853"],"abstract_inverted_index":{"Efficient":[0],"modelling":[1],"of":[2,15,18,25,32,44,65,72,108],"feature":[3,122,186,191,196],"interactions":[4],"underpins":[5],"supervised":[6],"learning":[7,26,144],"for":[8,29,74,177,208],"non-sequential":[9,174,210],"tasks,":[10,211],"characterized":[11],"by":[12],"a":[13,27,61,82],"lack":[14],"inherent":[16],"ordering":[17,107],"features":[19],"(variables).":[20],"The":[21],"brute":[22],"force":[23],"approach":[24],"parameter":[28],"each":[30],"interaction":[31],"every":[33],"order":[34,64],"comes":[35],"at":[36],"an":[37],"exponential":[38],"computational":[39],"and":[40,91,100,138,143,149],"memory":[41],"cost":[42],"(Curse":[43],"Dimensionality).":[45],"To":[46,116],"alleviate":[47],"this":[48,199],"issue,":[49],"it":[50,76],"has":[51],"been":[52],"proposed":[53,157],"to":[54,69,105,113,121,126,184,188,202],"implicitly":[55],"represent":[56,127],"the":[57,63,70,106,114,118,128,132,140,156,182],"model":[58],"parameters":[59],"as":[60,97,215],"tensor,":[62],"which":[66],"is":[67,153,200],"equal":[68],"number":[71],"features;":[73],"efficiency,":[75],"can":[77],"be":[78],"further":[79],"factorized":[80],"into":[81],"compact":[83],"Tensor":[84,93,98],"Train":[85],"(TT)":[86],"format.":[87],"However,":[88],"both":[89],"TT":[90],"other":[92,162],"Networks":[94],"(TNs),":[95],"such":[96,214],"Ring":[99],"Hierarchical":[101],"Tucker,":[102],"are":[103],"sensitive":[104],"their":[109],"indices":[110],"(and":[111],"hence":[112],"features).":[115],"establish":[117],"desired":[119],"invariance":[120],"ordering,":[123],"we":[124,180],"propose":[125],"weight":[129],"tensor":[130],"through":[131],"Canonical":[133],"Polyadic":[134],"(CP)":[135],"Decomposition":[136],"(CPD),":[137],"introduce":[139],"associated":[141],"inference":[142],"algorithms,":[145],"including":[146],"suitable":[147],"regularization":[148],"initialization":[150],"schemes.":[151],"It":[152],"demonstrated":[154],"that":[155],"CP-based":[158],"predictor":[159],"significantly":[160],"outperforms":[161],"TN-based":[163],"predictors":[164],"on":[165,172],"sparse":[166],"data":[167],"while":[168],"exhibiting":[169],"comparable":[170],"performance":[171,207],"dense":[173,209],"tasks.":[175],"Furthermore,":[176],"enhanced":[178],"expressiveness,":[179],"generalize":[181],"framework":[183],"allow":[185],"mapping":[187],"arbitrarily":[189],"high-dimensional":[190],"vectors.":[192],"In":[193],"conjunction":[194],"with":[195],"vector":[197],"normalization,":[198],"shown":[201],"yield":[203],"dramatic":[204],"improvements":[205],"in":[206],"matching":[212],"models":[213],"fully-connected":[216],"neural":[217],"networks.":[218]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}