{"id":"https://openalex.org/W1985529709","doi":"https://doi.org/10.1109/ijcnn.2014.6889472","title":"Tensor LRR based subspace clustering","display_name":"Tensor LRR based subspace clustering","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W1985529709","doi":"https://doi.org/10.1109/ijcnn.2014.6889472","mag":"1985529709"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889472","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5054504927","display_name":"Yifan Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I153230381","display_name":"Charles Sturt University","ror":"https://ror.org/00wfvh315","country_code":"AU","type":"education","lineage":["https://openalex.org/I153230381"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yifan Fu","raw_affiliation_strings":["Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia","institution_ids":["https://openalex.org/I153230381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015817857","display_name":"Junbin Gao","orcid":"https://orcid.org/0000-0001-9803-0256"},"institutions":[{"id":"https://openalex.org/I153230381","display_name":"Charles Sturt University","ror":"https://ror.org/00wfvh315","country_code":"AU","type":"education","lineage":["https://openalex.org/I153230381"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Junbin Gao","raw_affiliation_strings":["Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia","institution_ids":["https://openalex.org/I153230381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110211892","display_name":"David Tien","orcid":null},"institutions":[{"id":"https://openalex.org/I153230381","display_name":"Charles Sturt University","ror":"https://ror.org/00wfvh315","country_code":"AU","type":"education","lineage":["https://openalex.org/I153230381"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"David Tien","raw_affiliation_strings":["Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia","institution_ids":["https://openalex.org/I153230381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016399094","display_name":"Zhouchen Lin","orcid":"https://orcid.org/0000-0003-1493-7569"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhouchen Lin","raw_affiliation_strings":["Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, , China"],"affiliations":[{"raw_affiliation_string":"Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, , China","institution_ids":["https://openalex.org/I20231570"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.456,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":11,"citation_normalized_percentile":{"value":0.512195,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":86,"max":87},"biblio":{"volume":null,"issue":null,"first_page":"1877","last_page":"1884"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9995,"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":0.9995,"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":0.9994,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9959,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/rank","display_name":"Rank (graph theory)","score":0.54784656},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.49237883},{"id":"https://openalex.org/keywords/representation","display_name":"Representation","score":0.4789089},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral Clustering","score":0.45269424},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44420403}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.74085253},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7351279},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.71240824},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6061695},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.55699974},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.54784656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5272504},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.51861644},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.49237883},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4789089},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.45269424},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44420403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4235621},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42022616},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36782762},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.16403148},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08965051},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889472","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.45}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":32,"referenced_works":["https://openalex.org/W1555148682","https://openalex.org/W1574851760","https://openalex.org/W1950520880","https://openalex.org/W1981985525","https://openalex.org/W1997201895","https://openalex.org/W2003217181","https://openalex.org/W2024165284","https://openalex.org/W2053090063","https://openalex.org/W2068548513","https://openalex.org/W2072925128","https://openalex.org/W2084231918","https://openalex.org/W2085261163","https://openalex.org/W2100549954","https://openalex.org/W2102823806","https://openalex.org/W2103972604","https://openalex.org/W2105790475","https://openalex.org/W2121947440","https://openalex.org/W2124608575","https://openalex.org/W2125742596","https://openalex.org/W2136015602","https://openalex.org/W2140000690","https://openalex.org/W2142782401","https://openalex.org/W2146610201","https://openalex.org/W2164931791","https://openalex.org/W2165916500","https://openalex.org/W2165964979","https://openalex.org/W2294644361","https://openalex.org/W2616032753","https://openalex.org/W2951085447","https://openalex.org/W2952000622","https://openalex.org/W4250657332","https://openalex.org/W56210758"],"related_works":["https://openalex.org/W4287164812","https://openalex.org/W4285605394","https://openalex.org/W3213150849","https://openalex.org/W3172436493","https://openalex.org/W2957492749","https://openalex.org/W2896134808","https://openalex.org/W2386063599","https://openalex.org/W2025894073","https://openalex.org/W1975884855","https://openalex.org/W1887135636"],"abstract_inverted_index":{"Subspace":[0],"clustering":[1,85,117],"groups":[2],"a":[3,15,78,95,140],"set":[4,13],"of":[5,17,38,91,123,136],"samples":[6,24,44,58],"(vectors)":[7],"into":[8],"clusters":[9],"by":[10,86],"approximating":[11],"this":[12,62,74],"with":[14],"mixture":[16],"several":[18,159],"linear":[19,34],"subspaces,":[20],"so":[21],"that":[22,54,156],"the":[23,26,32,100,104,111,121,133],"in":[25,67],"same":[27,33],"cluster":[28],"are":[29,45],"drawn":[30],"from":[31,120,144],"subspace.":[35],"In":[36],"majority":[37],"existing":[39],"works":[40],"on":[41,149],"subspace":[42,84,142],"clustering,":[43],"simply":[46],"regarded":[47],"as":[48],"being":[49],"independent":[50],"and":[51,110,138,152],"identically":[52],"distributed,":[53],"is,":[55],"arbitrarily":[56],"ordering":[57],"when":[59],"necessary.":[60],"However,":[61],"setting":[63],"ignores":[64],"sample":[65],"correlations":[66],"their":[68],"original":[69],"spatial":[70,89,106,128],"structure.":[71],"To":[72],"address":[73],"issue,":[75],"we":[76],"propose":[77],"tensor":[79],"low-rank":[80],"representation":[81,97],"(TLRR)":[82],"for":[83,115],"keeping":[87],"available":[88],"information":[90],"data.":[92,146],"TLRR":[93,130,157],"seeks":[94],"lowest-rank":[96],"over":[98],"all":[99,126],"candidates":[101],"while":[102],"maintaining":[103],"inherent":[105],"structures":[107,135],"among":[108],"samples,":[109],"affinity":[112],"matrix":[113],"used":[114],"spectral":[116],"is":[118],"built":[119],"combination":[122],"similarities":[124],"along":[125],"data":[127,137],"directions.":[129],"better":[131],"captures":[132],"global":[134],"provides":[139],"robust":[141],"segmentation":[143],"corrupted":[145],"Experimental":[147],"results":[148],"both":[150],"synthetic":[151],"real-world":[153],"datasets":[154],"show":[155],"outperforms":[158],"established":[160],"state-of-the-art":[161],"methods.":[162]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1985529709","counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2024-12-12T04:55:41.963743","created_date":"2016-06-24"}