{"id":"https://openalex.org/W2965446129","doi":"https://doi.org/10.1145/3292500.3330881","title":"CoSTCo","display_name":"CoSTCo","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2965446129","doi":"https://doi.org/10.1145/3292500.3330881","mag":"2965446129"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330881","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330881","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330881","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330881","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071582484","display_name":"Hanpeng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hanpeng Liu","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101587352","display_name":"Yaguang Li","orcid":"https://orcid.org/0000-0003-3020-4437"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaguang Li","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050141186","display_name":"Michael Tsang","orcid":"https://orcid.org/0000-0003-2386-5210"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Tsang","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351175","display_name":"Yan Liu","orcid":"https://orcid.org/0000-0003-4242-4840"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071582484"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":4.1184,"has_fulltext":true,"cited_by_count":74,"citation_normalized_percentile":{"value":0.95848596,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"324","last_page":"334"},"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9050999879837036,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9006999731063843,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multilinear-map","display_name":"Multilinear map","score":0.9012792110443115},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7456138730049133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6399804353713989},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5856775045394897},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5818758010864258},{"id":"https://openalex.org/keywords/kronecker-delta","display_name":"Kronecker delta","score":0.5678862929344177},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.543104887008667},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.47982168197631836},{"id":"https://openalex.org/keywords/kronecker-product","display_name":"Kronecker product","score":0.4603317677974701},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.45290878415107727},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.4323578178882599},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40999364852905273},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34710514545440674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2481881082057953},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.1140781044960022},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07032328844070435}],"concepts":[{"id":"https://openalex.org/C84392682","wikidata":"https://www.wikidata.org/wiki/Q1952404","display_name":"Multilinear map","level":2,"score":0.9012792110443115},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7456138730049133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6399804353713989},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5856775045394897},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5818758010864258},{"id":"https://openalex.org/C39482219","wikidata":"https://www.wikidata.org/wiki/Q192826","display_name":"Kronecker delta","level":2,"score":0.5678862929344177},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.543104887008667},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47982168197631836},{"id":"https://openalex.org/C46030957","wikidata":"https://www.wikidata.org/wiki/Q1238125","display_name":"Kronecker product","level":3,"score":0.4603317677974701},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.45290878415107727},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.4323578178882599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40999364852905273},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34710514545440674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2481881082057953},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.1140781044960022},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07032328844070435},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3330881","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330881","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330881","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3292500.3330881","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3330881","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3330881","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2957356226","display_name":null,"funder_award_id":"IIS-1254206","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3800614899","display_name":"CyberSEES: Type 1: A Novel Machine Learning Framework for Urban Heat Island Causal Analysis: a Fusion of Observations and Physical Models","funder_award_id":"1539608","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5924908560","display_name":"CAREER: A Novel Framework for Knowledge Discovery from Time Series Data in Biology and Climate Science","funder_award_id":"1254206","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6647202427","display_name":null,"funder_award_id":"IIS-1539608","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332236","display_name":"Annenberg School for Communication and Journalism, University of Southern California","ror":"https://ror.org/03taz7m60"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965446129.pdf","grobid_xml":"https://content.openalex.org/works/W2965446129.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W23524565","https://openalex.org/W331379265","https://openalex.org/W564538011","https://openalex.org/W1520871589","https://openalex.org/W1619480882","https://openalex.org/W1673310716","https://openalex.org/W1814521481","https://openalex.org/W1912572177","https://openalex.org/W1963826206","https://openalex.org/W1969116741","https://openalex.org/W2017921654","https://openalex.org/W2024165284","https://openalex.org/W2044672016","https://openalex.org/W2049588365","https://openalex.org/W2078677240","https://openalex.org/W2089349245","https://openalex.org/W2091449379","https://openalex.org/W2096602764","https://openalex.org/W2103392911","https://openalex.org/W2104050041","https://openalex.org/W2116435618","https://openalex.org/W2121739212","https://openalex.org/W2126418337","https://openalex.org/W2127426251","https://openalex.org/W2130681737","https://openalex.org/W2144920235","https://openalex.org/W2167503371","https://openalex.org/W2167874303","https://openalex.org/W2170551306","https://openalex.org/W2402144811","https://openalex.org/W2515144511","https://openalex.org/W2552210686","https://openalex.org/W2562836854","https://openalex.org/W2605190428","https://openalex.org/W2728796024","https://openalex.org/W2739547565","https://openalex.org/W2742340639","https://openalex.org/W2765571454","https://openalex.org/W2889186417","https://openalex.org/W2950272073","https://openalex.org/W2951251599","https://openalex.org/W2952453038","https://openalex.org/W2962698165","https://openalex.org/W2962930448","https://openalex.org/W2963345431","https://openalex.org/W2963358464","https://openalex.org/W3103299328"],"related_works":["https://openalex.org/W123417539","https://openalex.org/W4233239985","https://openalex.org/W2079407403","https://openalex.org/W2060299328","https://openalex.org/W2117336295","https://openalex.org/W2073634779","https://openalex.org/W3102722572","https://openalex.org/W2090103374","https://openalex.org/W4283729979","https://openalex.org/W1564288589"],"abstract_inverted_index":{"Low-rank":[0],"tensor":[1,11,24,77,209],"factorization":[2,17],"has":[3],"been":[4],"widely":[5],"used":[6],"for":[7,61],"many":[8,42],"real":[9,30,121,189],"world":[10,31,122,190],"completion":[12,210],"problems.":[13],"While":[14],"most":[15],"existing":[16],"models":[18,50],"assume":[19],"a":[20,81,88,126],"multilinearity":[21],"relationship":[22],"between":[23],"entries":[25],"and":[26,96,108,155,194,206],"their":[27],"corresponding":[28],"factors,":[29],"tensors":[32,154,193],"tend":[33],"to":[34,79,90,110,115,148,160],"have":[35],"more":[36],"complex":[37,94,151],"interactions":[38,95,152],"than":[39,53],"multilinearity.":[40],"In":[41,101],"recent":[43],"works,":[44],"it":[45,170],"is":[46,167],"observed":[47],"that":[48,75,199],"multilinear":[49],"perform":[51],"worse":[52],"nonlinear":[54,207],"models.":[55],"We":[56,124,183],"identify":[57],"one":[58],"potential":[59],"reason":[60],"this":[62,85],"inferior":[63],"performance:":[64],"the":[65,70,76,93,98,103,143,150,162,195],"nonlinearity":[66],"inside":[67,153],"data":[68],"obfuscates":[69],"underlying":[71],"low-rank":[72,99,164],"structure":[73],"such":[74,179],"seems":[78],"be":[80,106],"high-rank":[82],"tensor.":[83],"Solving":[84],"problem":[86],"requires":[87],"model":[89,104,141,149,201],"simultaneously":[91],"capture":[92],"preserve":[97,161],"structure.":[100,165],"addition,":[102],"should":[105],"scalable":[107,168],"robust":[109],"missing":[111],"observations":[112],"in":[113],"order":[114],"learn":[116],"from":[117],"large":[118,191],"yet":[119],"sparse":[120,192],"tensors.":[123],"propose":[125],"novel":[127],"convolutional":[128],"neural":[129],"network":[130],"(CNN)":[131],"based":[132],"model,":[133],"named":[134],"CoSTCo":[135,166],"(Convolutional":[136],"Sparse":[137],"Tensor":[138],"Completion).":[139],"Our":[140],"leverages":[142],"expressive":[144],"power":[145],"of":[146],"CNN":[147],"its":[156],"parameter":[157],"sharing":[158],"scheme":[159],"desired":[163],"as":[169,180],"does":[171],"not":[172],"involve":[173],"computation-":[174],"or":[175],"memory-":[176],"heavy":[177],"tasks":[178],"Kronecker":[181],"product.":[182],"conduct":[184],"extensive":[185],"experiments":[186],"on":[187],"several":[188],"experimental":[196],"results":[197],"show":[198],"our":[200],"clearly":[202],"outperforms":[203],"both":[204],"linear":[205],"state-of-the-art":[208],"methods.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":10}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2019-08-13T00:00:00"}