{"id":"https://openalex.org/W2792886831","doi":"https://doi.org/10.1109/camsap.2017.8313222","title":"Low-Rank tensor regression: Scalability and applications","display_name":"Low-Rank tensor regression: Scalability and applications","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2792886831","doi":"https://doi.org/10.1109/camsap.2017.8313222","mag":"2792886831"},"language":"en","primary_location":{"id":"doi:10.1109/camsap.2017.8313222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap.2017.8313222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"},"type":"conference-paper","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/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":true,"raw_author_name":"Yan Liu","raw_affiliation_strings":["Computer Science Department, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100351175"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.1584,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.41101695,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9783999919891357,"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/tensor","display_name":"Tensor (intrinsic definition)","score":0.8272815942764282},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7033188343048096},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6907919645309448},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.647142767906189},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5464426875114441},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5315449237823486},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5285807251930237},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.42915764451026917},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.41540780663490295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3483039140701294},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34778285026550293},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3441930413246155},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3319939374923706},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23016357421875},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14235302805900574},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07077530026435852}],"concepts":[{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.8272815942764282},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7033188343048096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6907919645309448},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.647142767906189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5464426875114441},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5315449237823486},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5285807251930237},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.42915764451026917},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.41540780663490295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3483039140701294},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34778285026550293},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3441930413246155},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3319939374923706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23016357421875},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14235302805900574},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07077530026435852},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/camsap.2017.8313222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camsap.2017.8313222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1520871589","https://openalex.org/W1912572177","https://openalex.org/W1970176196","https://openalex.org/W1985026434","https://openalex.org/W1999846158","https://openalex.org/W2013912476","https://openalex.org/W2024165284","https://openalex.org/W2030628896","https://openalex.org/W2037360998","https://openalex.org/W2037842665","https://openalex.org/W2038497950","https://openalex.org/W2054443446","https://openalex.org/W2061370212","https://openalex.org/W2074624752","https://openalex.org/W2078626246","https://openalex.org/W2079705627","https://openalex.org/W2098132613","https://openalex.org/W2103325283","https://openalex.org/W2103367708","https://openalex.org/W2110121428","https://openalex.org/W2113055885","https://openalex.org/W2129297793","https://openalex.org/W2130681737","https://openalex.org/W2136002544","https://openalex.org/W2160634266","https://openalex.org/W2169162463","https://openalex.org/W2468422810","https://openalex.org/W2480579674","https://openalex.org/W2951251599","https://openalex.org/W2963322354","https://openalex.org/W3098004101","https://openalex.org/W3102581530","https://openalex.org/W4237552847","https://openalex.org/W6639939241","https://openalex.org/W6679272984","https://openalex.org/W6679363028","https://openalex.org/W6684029298","https://openalex.org/W6685325116","https://openalex.org/W6720207886"],"related_works":["https://openalex.org/W2950186459","https://openalex.org/W2170114491","https://openalex.org/W2897298721","https://openalex.org/W2242624680","https://openalex.org/W2136127937","https://openalex.org/W4290987221","https://openalex.org/W2216309014","https://openalex.org/W2569661359","https://openalex.org/W3199841771","https://openalex.org/W4286971555"],"abstract_inverted_index":{"With":[0],"the":[1,32],"development":[2],"of":[3,10,43],"sensor":[4],"and":[5],"satellite":[6],"technologies,":[7],"massive":[8],"amount":[9],"multiway":[11],"data":[12],"emerges":[13],"in":[14,51],"many":[15],"applications.":[16],"Low-rank":[17,65],"tensor":[18,26,49,76],"regression,":[19],"as":[20],"a":[21,41,57],"powerful":[22],"technique":[23],"for":[24,46,60,71,79],"analyzing":[25],"data,":[27],"attracted":[28],"significant":[29],"interest":[30],"from":[31],"machine":[33],"learning":[34,53],"community.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39],"discuss":[40],"series":[42],"fast":[44],"algorithms":[45],"solving":[47],"low-rank":[48],"regression":[50],"different":[52],"scenarios,":[54],"including":[55],"(a)":[56],"greedy":[58],"algorithm":[59,70],"batch":[61],"learning;":[62,73],"(b)":[63],"Accelerated":[64],"Tensor":[66],"Online":[67],"Learning":[68],"(ALTO)":[69],"online":[72],"(c)":[74],"subsampled":[75],"projected":[77],"gradient":[78],"memory":[80],"efficient":[81],"learning.":[82]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
