{"id":"https://openalex.org/W2747622561","doi":"https://doi.org/10.1109/lsp.2017.2741509","title":"Active Orthogonal Matching Pursuit for Sparse Subspace Clustering","display_name":"Active Orthogonal Matching Pursuit for Sparse Subspace Clustering","publication_year":2017,"publication_date":"2017-08-29","ids":{"openalex":"https://openalex.org/W2747622561","doi":"https://doi.org/10.1109/lsp.2017.2741509","mag":"2747622561"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2017.2741509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2741509","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1708.04764","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100763782","display_name":"Yanxi Chen","orcid":"https://orcid.org/0000-0003-0610-8103"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanxi Chen","raw_affiliation_strings":["Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357060","display_name":"Gen Li","orcid":"https://orcid.org/0009-0005-9782-7649"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gen Li","raw_affiliation_strings":["Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100621681","display_name":"Yuantao Gu","orcid":"https://orcid.org/0000-0002-8427-1021"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuantao Gu","raw_affiliation_strings":["Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100763782"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":4.6851,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.95443246,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"25","issue":"2","first_page":"164","last_page":"168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980999827384949,"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":0.9979000091552734,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996999979019165,"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/matching-pursuit","display_name":"Matching pursuit","score":0.9234331846237183},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7880420684814453},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.6180508136749268},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5977963805198669},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.5643742084503174},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5404080152511597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5192520618438721},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4832042455673218},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4752350151538849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47311636805534363},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.470243364572525},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44289320707321167},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41597995162010193},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2919374406337738},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.07818618416786194}],"concepts":[{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.9234331846237183},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7880420684814453},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.6180508136749268},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5977963805198669},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.5643742084503174},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5404080152511597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5192520618438721},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4832042455673218},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4752350151538849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47311636805534363},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.470243364572525},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44289320707321167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41597995162010193},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2919374406337738},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.07818618416786194},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2017.2741509","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2741509","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1708.04764","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.04764","pdf_url":"https://arxiv.org/pdf/1708.04764","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1708.04764","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.04764","pdf_url":"https://arxiv.org/pdf/1708.04764","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":[{"id":"https://openalex.org/G1822711454","display_name":null,"funder_award_id":"61371137","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4609625212","display_name":null,"funder_award_id":"61531166005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7777656554","display_name":null,"funder_award_id":"61571263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8372767878","display_name":null,"funder_award_id":"51459003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1600471557","https://openalex.org/W1781773254","https://openalex.org/W1826721227","https://openalex.org/W1884731728","https://openalex.org/W1977196460","https://openalex.org/W1981458038","https://openalex.org/W1993962865","https://openalex.org/W1997201895","https://openalex.org/W2054199929","https://openalex.org/W2088025572","https://openalex.org/W2103943817","https://openalex.org/W2126761607","https://openalex.org/W2127271355","https://openalex.org/W2132014503","https://openalex.org/W2132914434","https://openalex.org/W2139054653","https://openalex.org/W2144902590","https://openalex.org/W2160915541","https://openalex.org/W2162198533","https://openalex.org/W2407917165","https://openalex.org/W2532206188","https://openalex.org/W2541308381","https://openalex.org/W2561426102","https://openalex.org/W2607365582","https://openalex.org/W2719480723","https://openalex.org/W2951184730","https://openalex.org/W2951854417","https://openalex.org/W2952300832","https://openalex.org/W2962911132","https://openalex.org/W2963496380","https://openalex.org/W2963840432","https://openalex.org/W2964193132","https://openalex.org/W3102566946","https://openalex.org/W3105745294","https://openalex.org/W4250657332","https://openalex.org/W6638071513","https://openalex.org/W6638654622","https://openalex.org/W6675666693","https://openalex.org/W6679903135","https://openalex.org/W6681275918","https://openalex.org/W6704231826","https://openalex.org/W6729237173","https://openalex.org/W6786535214"],"related_works":["https://openalex.org/W3100286349","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W4294291164","https://openalex.org/W3172436493","https://openalex.org/W1887135636","https://openalex.org/W4287164812","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849"],"abstract_inverted_index":{"Sparse":[0],"subspace":[1],"clustering":[2,9,44,63],"(SSC)":[3],"is":[4],"a":[5,15,57,107],"state-of-the-art":[6],"method":[7],"for":[8],"high-dimensional":[10],"data":[11,70,75,119,122],"points":[12,71,76],"lying":[13],"in":[14,46,77],"union":[16],"of":[17,36,48,65,88,96,130],"low-dimensional":[18],"subspaces.":[19],"However,":[20],"while":[21,81],"\u2113":[22],"<sub":[23],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[24],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[25],"optimization-based":[26],"SSC":[27,41],"algorithms":[28],"suffer":[29],"from":[30],"high":[31],"computational":[32,86],"complexity,":[33],"other":[34],"variants":[35],"SSC,":[37],"such":[38],"as":[39],"orthogonal-matching-pursuit-based":[40],"(OMP-SSC),":[42],"lose":[43],"accuracy":[45,64],"pursuit":[47,90],"improving":[49],"time":[50],"efficiency.":[51],"In":[52],"this":[53],"letter,":[54],"we":[55],"propose":[56],"novel":[58],"active":[59,104,133],"OMP-SSC,":[60],"which":[61],"improves":[62],"OMP-SSC":[66],"by":[67],"adaptively":[68],"updating":[69],"and":[72,99,112,120,126],"randomly":[73],"dropping":[74],"the":[78,84,128,131],"OMP":[79],"process,":[80],"still":[82],"enjoying":[83],"low":[85],"complexity":[87],"greedy":[89],"algorithms.":[91],"We":[92],"provide":[93],"heuristic":[94],"analysis":[95],"our":[97,124],"approach":[98],"explain":[100],"how":[101],"these":[102],"two":[103],"steps":[105],"achieve":[106],"better":[108],"tradeoff":[109],"between":[110],"connectivity":[111],"separation.":[113],"Numerical":[114],"results":[115],"on":[116],"both":[117],"synthetic":[118],"real-world":[121],"validate":[123],"analyses":[125],"show":[127],"advantages":[129],"proposed":[132],"algorithm.":[134]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
