{"id":"https://openalex.org/W4396599140","doi":"https://doi.org/10.1109/tpami.2024.3396386","title":"Machine Learning With Tree Tensor Networks, CP Rank Constraints, and Tensor Dropout","display_name":"Machine Learning With Tree Tensor Networks, CP Rank Constraints, and Tensor Dropout","publication_year":2024,"publication_date":"2024-05-02","ids":{"openalex":"https://openalex.org/W4396599140","doi":"https://doi.org/10.1109/tpami.2024.3396386","pmid":"https://pubmed.ncbi.nlm.nih.gov/38696289"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3396386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3396386","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100353675","display_name":"Hao Chen","orcid":"https://orcid.org/0009-0002-1390-0625"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Hao Chen","raw_affiliation_strings":["Department of Physics, ETH Zurich, Zürich, Switzerland"],"affiliations":[{"raw_affiliation_string":"Department of Physics, ETH Zurich, Zürich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019126088","display_name":"Thomas Barthel","orcid":"https://orcid.org/0000-0001-5351-4011"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas Barthel","raw_affiliation_strings":["Department of Physics and Duke Quantum Center, Duke University, Durham, NC, USA","Department of Physics & Duke Quantum Center, Duke University, Durham, North Carolina 27708, USA"],"affiliations":[{"raw_affiliation_string":"Department of Physics and Duke Quantum Center, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Department of Physics & Duke Quantum Center, Duke University, Durham, North Carolina 27708, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100353675"],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":3.1606,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92410182,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"46","issue":"12","first_page":"7825","last_page":"7832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9937999844551086,"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"}},"topics":[{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9937999844551086,"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/T12303","display_name":"Tensor decomposition and applications","score":0.9905999898910522,"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":0.9082000255584717,"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/dropout","display_name":"Dropout (neural networks)","score":0.6959778666496277},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6490784883499146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6066836714744568},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5510370135307312},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4986531734466553},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.47314321994781494},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.45928287506103516},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44052404165267944},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38487672805786133},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.22404086589813232},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.0906316339969635}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.6959778666496277},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6490784883499146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6066836714744568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5510370135307312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4986531734466553},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.47314321994781494},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.45928287506103516},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44052404165267944},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38487672805786133},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.22404086589813232},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0906316339969635}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2024.3396386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3396386","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:38696289","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38696289","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":103,"referenced_works":["https://openalex.org/W391985582","https://openalex.org/W1503398984","https://openalex.org/W1522301498","https://openalex.org/W1570334424","https://openalex.org/W1621265897","https://openalex.org/W1976879565","https://openalex.org/W1988485873","https://openalex.org/W1993482030","https://openalex.org/W1995716588","https://openalex.org/W2000215628","https://openalex.org/W2024165284","https://openalex.org/W2033368244","https://openalex.org/W2035298342","https://openalex.org/W2036463035","https://openalex.org/W2037768897","https://openalex.org/W2039434005","https://openalex.org/W2039973605","https://openalex.org/W2048364886","https://openalex.org/W2062903373","https://openalex.org/W2068894496","https://openalex.org/W2069143585","https://openalex.org/W2074426935","https://openalex.org/W2088025933","https://openalex.org/W2090558939","https://openalex.org/W2093774709","https://openalex.org/W2095705004","https://openalex.org/W2112796928","https://openalex.org/W2122816100","https://openalex.org/W2132267493","https://openalex.org/W2133656308","https://openalex.org/W2164812020","https://openalex.org/W2258054274","https://openalex.org/W2295598076","https://openalex.org/W2618530766","https://openalex.org/W2750384547","https://openalex.org/W2753545915","https://openalex.org/W2782213776","https://openalex.org/W2785523195","https://openalex.org/W2794602324","https://openalex.org/W2797105324","https://openalex.org/W2910259907","https://openalex.org/W2922105745","https://openalex.org/W2923124012","https://openalex.org/W2949757588","https://openalex.org/W2951542569","https://openalex.org/W3015983231","https://openalex.org/W3037108023","https://openalex.org/W3087264907","https://openalex.org/W3098662938","https://openalex.org/W3099956647","https://openalex.org/W3100068159","https://openalex.org/W3100993774","https://openalex.org/W3103289362","https://openalex.org/W3103713775","https://openalex.org/W3106011565","https://openalex.org/W3110294450","https://openalex.org/W3118897825","https://openalex.org/W3134405558","https://openalex.org/W3137884659","https://openalex.org/W3166901602","https://openalex.org/W3167172260","https://openalex.org/W3173538149","https://openalex.org/W3190586500","https://openalex.org/W3192183957","https://openalex.org/W3193878271","https://openalex.org/W3195630663","https://openalex.org/W3213318058","https://openalex.org/W4221149907","https://openalex.org/W4280591843","https://openalex.org/W4281875249","https://openalex.org/W4285483469","https://openalex.org/W4287724305","https://openalex.org/W4292222267","https://openalex.org/W4295927811","https://openalex.org/W4300979811","https://openalex.org/W4301075235","https://openalex.org/W4308968493","https://openalex.org/W4327743729","https://openalex.org/W4362598015","https://openalex.org/W4386284671","https://openalex.org/W4388411486","https://openalex.org/W4392782033","https://openalex.org/W4396905016","https://openalex.org/W6600089797","https://openalex.org/W6631190155","https://openalex.org/W6634180991","https://openalex.org/W6638868411","https://openalex.org/W6674330103","https://openalex.org/W6729942461","https://openalex.org/W6739028767","https://openalex.org/W6743688258","https://openalex.org/W6747620207","https://openalex.org/W6757817989","https://openalex.org/W6764213378","https://openalex.org/W6775917861","https://openalex.org/W6780583830","https://openalex.org/W6786459191","https://openalex.org/W6788334867","https://openalex.org/W6810259426","https://openalex.org/W6838605497","https://openalex.org/W6839457639","https://openalex.org/W6845025590","https://openalex.org/W6851978065"],"related_works":["https://openalex.org/W2950186459","https://openalex.org/W2170114491","https://openalex.org/W2242624680","https://openalex.org/W2136127937","https://openalex.org/W2897298721","https://openalex.org/W4290987221","https://openalex.org/W2216309014","https://openalex.org/W2569661359","https://openalex.org/W3199841771","https://openalex.org/W4286971555"],"abstract_inverted_index":{"Tensor":[0],"networks":[1,80],"developed":[2],"in":[3,28,45,71,92,104],"the":[4,46,63,69,136,184],"context":[5,47],"of":[6,20,22,35,48,68,121,128,140,153],"condensed":[7],"matter":[8],"physics":[9],"try":[10],"to":[11,99,162,175],"approximate":[12],"order-":[13],"N":[14,29],"tensors":[15,70],"with":[16,82,112,123,178],"a":[17,33,117],"reduced":[18,58],"number":[19,152],"degrees":[21],"freedom":[23],"that":[24],"is":[25,97],"only":[26],"polynomial":[27],"and":[30,86,158,168],"arranged":[31],"as":[32],"network":[34,133],"partially":[36],"contracted":[37],"smaller":[38],"tensors.":[39],"As":[40],"we":[41,75],"have":[42,148],"recently":[43],"demonstrated":[44],"quantum":[49],"many-body":[50],"physics,":[51],"computation":[52,125,170],"costs":[53],"can":[54,89,155],"be":[55,90,156],"further":[56],"substantially":[57,182],"by":[59],"imposing":[60],"constraints":[61,85,147],"on":[62],"canonical":[64],"polyadic":[65],"(CP)":[66],"rank":[67,84,146],"such":[72],"networks.":[73,143],"Here,":[74],"demonstrate":[76],"how":[77],"tree":[78],"tensor":[79,87,132],"(TTN)":[81],"CP":[83,145],"dropout":[88],"used":[91],"machine":[93],"learning.":[94],"The":[95,144,151],"approach":[96],"found":[98],"outperform":[100],"other":[101],"tensor-network-based":[102],"methods":[103],"Fashion-MNIST":[105],"image":[106],"classification.":[107],"A":[108],"low-rank":[109],"TTN":[110],"classifier":[111],"branching":[113,180],"ratio":[114],"b=4":[115],"reaches":[116],"test":[118],"set":[119],"accuracy":[120],"90.3%":[122],"low":[124],"costs.":[126,171],"Consisting":[127],"mostly":[129],"linear":[130],"elements,":[131],"classifiers":[134],"avoid":[135],"vanishing":[137],"gradient":[138],"problem":[139],"deep":[141],"neural":[142],"additional":[149],"advantages:":[150],"parameters":[154],"decreased":[157],"tuned":[159],"more":[160],"freely":[161],"control":[163],"overfitting,":[164],"improve":[165],"generalization":[166],"properties,":[167],"reduce":[169],"They":[172],"allow":[173],"us":[174],"employ":[176],"trees":[177],"large":[179],"ratios,":[181],"improving":[183],"representation":[185],"power.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}