{"id":"https://openalex.org/W3093733273","doi":"https://doi.org/10.1109/acssc.2018.8645348","title":"Randomized Robust matrix Completion for the Community Detection Problem","display_name":"Randomized Robust matrix Completion for the Community Detection Problem","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W3093733273","doi":"https://doi.org/10.1109/acssc.2018.8645348","mag":"3093733273"},"language":"en","primary_location":{"id":"doi:10.1109/acssc.2018.8645348","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2018.8645348","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"},"type":"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/A5029569030","display_name":"Adel Karimian","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Adel Karimian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101657195","display_name":"Mostafa Rahmani","orcid":"https://orcid.org/0000-0002-4140-383X"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mostafa Rahmani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039015394","display_name":"Andre Beckus","orcid":"https://orcid.org/0000-0001-7182-0776"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andre Beckus","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003612688","display_name":"George Atia","orcid":"https://orcid.org/0000-0001-7958-9855"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George K. Atia","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029569030"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43553009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"49","issue":null,"first_page":"2099","last_page":"2103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9894999861717224,"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/adjacency-matrix","display_name":"Adjacency matrix","score":0.782339334487915},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.728301465511322},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.5919227600097656},{"id":"https://openalex.org/keywords/randomized-algorithm","display_name":"Randomized algorithm","score":0.5197274684906006},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.5010905265808105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47764599323272705},{"id":"https://openalex.org/keywords/stochastic-block-model","display_name":"Stochastic block model","score":0.45828360319137573},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.449280321598053},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.4472968876361847},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4448763430118561},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4447779059410095},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4447691738605499},{"id":"https://openalex.org/keywords/distance-matrix","display_name":"Distance matrix","score":0.4279100298881531},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3974258303642273},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33142969012260437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2615911364555359}],"concepts":[{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.782339334487915},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.728301465511322},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.5919227600097656},{"id":"https://openalex.org/C128669082","wikidata":"https://www.wikidata.org/wiki/Q583461","display_name":"Randomized algorithm","level":2,"score":0.5197274684906006},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.5010905265808105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47764599323272705},{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.45828360319137573},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.449280321598053},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.4472968876361847},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4448763430118561},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4447779059410095},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4447691738605499},{"id":"https://openalex.org/C111208986","wikidata":"https://www.wikidata.org/wiki/Q901698","display_name":"Distance matrix","level":2,"score":0.4279100298881531},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3974258303642273},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33142969012260437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2615911364555359},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acssc.2018.8645348","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acssc.2018.8645348","pdf_url":null,"source":{"id":"https://openalex.org/S4363608623","display_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 52nd Asilomar Conference on Signals, Systems, and Computers","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":57,"referenced_works":["https://openalex.org/W185836397","https://openalex.org/W272277767","https://openalex.org/W1605211498","https://openalex.org/W1664520935","https://openalex.org/W1760108839","https://openalex.org/W1771423625","https://openalex.org/W1992419399","https://openalex.org/W1993962865","https://openalex.org/W2003753589","https://openalex.org/W2024128809","https://openalex.org/W2067462817","https://openalex.org/W2084439502","https://openalex.org/W2087445541","https://openalex.org/W2096608935","https://openalex.org/W2098509290","https://openalex.org/W2102907934","https://openalex.org/W2117756735","https://openalex.org/W2119233169","https://openalex.org/W2132914434","https://openalex.org/W2136384819","https://openalex.org/W2145962650","https://openalex.org/W2152402969","https://openalex.org/W2155813684","https://openalex.org/W2158121106","https://openalex.org/W2277420077","https://openalex.org/W2290805605","https://openalex.org/W2470359451","https://openalex.org/W2478708596","https://openalex.org/W2519496013","https://openalex.org/W2524039959","https://openalex.org/W2540057053","https://openalex.org/W2611993295","https://openalex.org/W2614891641","https://openalex.org/W2914959486","https://openalex.org/W2951271819","https://openalex.org/W2962763602","https://openalex.org/W2962778482","https://openalex.org/W2962839800","https://openalex.org/W2963332078","https://openalex.org/W2963359241","https://openalex.org/W2963363076","https://openalex.org/W3009483570","https://openalex.org/W3103168990","https://openalex.org/W3104624268","https://openalex.org/W3123255541","https://openalex.org/W3126033509","https://openalex.org/W4317668321","https://openalex.org/W6634113119","https://openalex.org/W6638079774","https://openalex.org/W6640570641","https://openalex.org/W6658883175","https://openalex.org/W6682218280","https://openalex.org/W6694529670","https://openalex.org/W6720261860","https://openalex.org/W6726721034","https://openalex.org/W6729127520","https://openalex.org/W6737966065"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W1531601525","https://openalex.org/W2082020694","https://openalex.org/W2970165350","https://openalex.org/W2538138540","https://openalex.org/W3006451817","https://openalex.org/W2397487909","https://openalex.org/W2150386905","https://openalex.org/W2796500753"],"abstract_inverted_index":{"This":[0],"paper":[1],"focuses":[2],"on":[3,62],"the":[4,44,85,88,109,114],"unsupervised":[5],"clustering":[6,21,89],"of":[7,87],"large":[8],"partially":[9,96],"observed":[10,97],"graphs.":[11],"We":[12],"propose":[13],"a":[14,20,26,32,51,68,73,95],"provable":[15],"randomized":[16],"framework":[17],"in":[18],"which":[19,81],"algorithm":[22,78,90],"is":[23,38,48,79],"applied":[24],"to":[25,123],"graph's":[27],"adjacency":[28,100],"matrix":[29,53,101],"generated":[30],"from":[31,117],"stochastic":[33],"block":[34],"model.":[35],"A":[36,102],"sub-matrix":[37],"constructed":[39],"using":[40,50,67],"random":[41,75],"sampling,":[42],"and":[43],"low":[45,64],"rank":[46,65],"component":[47,66],"found":[49],"convex-optimization-based":[52],"completion":[54],"algorithm.":[55],"The":[56],"clusters":[57],"are":[58],"then":[59],"identified":[60],"based":[61],"this":[63],"correlation-based":[69],"retrieval":[70],"step.":[71],"Additionally,":[72],"new":[74],"node":[76],"sampling":[77],"presented":[80],"significantly":[82],"improves":[83],"upon":[84],"performance":[86],"with":[91,99],"unbalanced":[92],"data.":[93],"Given":[94],"graph":[98],"\u2208":[103],"R":[104],"<sup":[105,119],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[106,120],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">N\u00d7N</sup>":[107],",":[108],"proposed":[110],"approach":[111],"can":[112],"reduce":[113],"computational":[115],"complexity":[116],"O(N":[118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[121],")":[122],"O(N).":[124]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}