{"id":"https://openalex.org/W3207658688","doi":"https://doi.org/10.1109/tkde.2020.3024099","title":"A Multi-Criteria Approach for Fast and Robust Representative Selection from Manifolds","display_name":"A Multi-Criteria Approach for Fast and Robust Representative Selection from Manifolds","publication_year":2020,"publication_date":"2020-09-15","ids":{"openalex":"https://openalex.org/W3207658688","doi":"https://doi.org/10.1109/tkde.2020.3024099","mag":"3207658688"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2020.3024099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3024099","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5042356096","display_name":"Mahlagha Sedghi","orcid":"https://orcid.org/0000-0003-4466-3079"},"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":"Mahlagha Sedghi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"raw_orcid":"https://orcid.org/0000-0003-4466-3079","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036799400","display_name":"Michael Georgiopoulos","orcid":"https://orcid.org/0009-0002-8840-0123"},"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":"Michael Georgiopoulos","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 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, FL, USA"],"raw_orcid":"https://orcid.org/0000-0001-7958-9855","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":{"value":2045,"currency":"USD","value_usd":2045},"apc_paid":null,"fwci":0.5687,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.77073276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"34","issue":"7","first_page":"3057","last_page":"3071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9962999820709229,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7526377439498901},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7063288688659668},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5910413265228271},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5702207684516907},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5365139842033386},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5127714276313782},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49641233682632446},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.45751187205314636},{"id":"https://openalex.org/keywords/data-redundancy","display_name":"Data redundancy","score":0.41982191801071167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40791600942611694},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36909231543540955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33779653906822205},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33032160997390747}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7526377439498901},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7063288688659668},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5910413265228271},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5702207684516907},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5365139842033386},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5127714276313782},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49641233682632446},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.45751187205314636},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.41982191801071167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40791600942611694},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36909231543540955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33779653906822205},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33032160997390747},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2020.3024099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3024099","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2826312378","display_name":"Collaborative Research: Florida IT Pathways to Success (Flit-Path)","funder_award_id":"1643835","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3157310737","display_name":"CAREER: Inference-Driven Data Processing and Acquisition: Scalability, Robustness and Control","funder_award_id":"1552497","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5363861886","display_name":"CAMP-YES (Career Advancement Mentoring Program for Young Entrepreneur and Scholars)","funder_award_id":"1356233","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7369117273","display_name":"UCF COMPASS (Convincing Outstanding-Math-Potential Admits to Succeed in STEM)","funder_award_id":"1161228","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W87092222","https://openalex.org/W104847522","https://openalex.org/W141957561","https://openalex.org/W1497599070","https://openalex.org/W1533072162","https://openalex.org/W1588401315","https://openalex.org/W1593443060","https://openalex.org/W1890834058","https://openalex.org/W1966872876","https://openalex.org/W1969602371","https://openalex.org/W1990319151","https://openalex.org/W1993962865","https://openalex.org/W1997164082","https://openalex.org/W1997201895","https://openalex.org/W1998269045","https://openalex.org/W2005803955","https://openalex.org/W2007800125","https://openalex.org/W2008205484","https://openalex.org/W2016182223","https://openalex.org/W2043661478","https://openalex.org/W2046793177","https://openalex.org/W2089135543","https://openalex.org/W2092736096","https://openalex.org/W2099111195","https://openalex.org/W2107826452","https://openalex.org/W2110373679","https://openalex.org/W2113642685","https://openalex.org/W2119233169","https://openalex.org/W2123921160","https://openalex.org/W2145962650","https://openalex.org/W2157305458","https://openalex.org/W2161984370","https://openalex.org/W2164278908","https://openalex.org/W2165232124","https://openalex.org/W2187580259","https://openalex.org/W2288699839","https://openalex.org/W2294798173","https://openalex.org/W2319358180","https://openalex.org/W2478708596","https://openalex.org/W2536599074","https://openalex.org/W2536769834","https://openalex.org/W2560092514","https://openalex.org/W2573426660","https://openalex.org/W2593628007","https://openalex.org/W2732039841","https://openalex.org/W2763633631","https://openalex.org/W2790755967","https://openalex.org/W2807479031","https://openalex.org/W2842078607","https://openalex.org/W2898230917","https://openalex.org/W2898633488","https://openalex.org/W2900393952","https://openalex.org/W2909227050","https://openalex.org/W2921315455","https://openalex.org/W2951815872","https://openalex.org/W2963877232","https://openalex.org/W2972877421","https://openalex.org/W2999998852","https://openalex.org/W3009483570","https://openalex.org/W3016538843","https://openalex.org/W3100542508","https://openalex.org/W3120740533","https://openalex.org/W3125520697","https://openalex.org/W4239875977","https://openalex.org/W4244670803","https://openalex.org/W4292230442","https://openalex.org/W4292363360","https://openalex.org/W4300183430","https://openalex.org/W4301850403","https://openalex.org/W6603183647","https://openalex.org/W6635310694","https://openalex.org/W6649696512","https://openalex.org/W6650267568","https://openalex.org/W6651530379","https://openalex.org/W6673731664","https://openalex.org/W6676392525","https://openalex.org/W6683265229","https://openalex.org/W6686821501","https://openalex.org/W6696227623","https://openalex.org/W6737966065","https://openalex.org/W6740697456"],"related_works":["https://openalex.org/W2002428578","https://openalex.org/W2897258045","https://openalex.org/W2018406690","https://openalex.org/W2072332896","https://openalex.org/W2951748633","https://openalex.org/W2542042335","https://openalex.org/W4292309272","https://openalex.org/W2057691131","https://openalex.org/W2952039693","https://openalex.org/W4280621979"],"abstract_inverted_index":{"The":[0],"problem":[1],"of":[2,22,53,75,81,102,116,132,149],"representative":[3,44,151],"selection":[4,18,45,67],"amounts":[5],"to":[6,16,137,160,178],"sampling":[7,28],"few":[8],"informative":[9],"exemplars":[10],"from":[11],"large":[12],"datasets.":[13],"Existing":[14],"approaches":[15],"data":[17,26,117,175],"often":[19],"fall":[20],"short":[21],"simultaneously":[23],"handling":[24],"non-linear":[25],"structures,":[27],"concise":[29],"and":[30,35,87,106,173],"non-redundant":[31],"subsets,":[32],"rejecting":[33],"outliers,":[34],"yielding":[36],"interpretable":[37],"outcomes.":[38],"This":[39],"paper":[40],"presents":[41],"a":[42,59,65,113,120,127,150],"novel":[43,60],"approach,":[46],"dubbed":[47],"MOSAIC,":[48],"for":[49],"drawing":[50],"descriptive":[51],"sketches":[52],"arbitrary":[54],"manifold":[55],"structures.":[56],"Resting":[57],"upon":[58],"quadratic":[61],"formulation,":[62],"MOSAIC":[63],"advances":[64],"multi-criteria":[66],"approach":[68],"that":[69,108],"maximizes":[70],"the":[71,76,82,103,109,133,146],"global":[72],"representation":[73],"power":[74],"sampled":[77,110],"subset,":[78],"ensures":[79],"novelty":[80],"samples":[83],"by":[84,91],"minimizing":[85],"redundancy,":[86],"rejects":[88],"disruptive":[89],"information":[90],"effectively":[92],"detecting":[93],"outliers.":[94],"Theoretical":[95],"analyses":[96],"shed":[97],"light":[98],"on":[99,170],"geometrical":[100],"characterization":[101],"obtained":[104],"sketch":[105],"reveal":[107],"representatives":[111],"maximize":[112],"well-defined":[114],"notion":[115],"coverage":[118],"in":[119,144],"transformed":[121],"space.":[122],"In":[123],"addition,":[124],"we":[125],"present":[126],"highly":[128],"scalable":[129],"randomized":[130],"implementation":[131],"proposed":[134],"algorithm":[135],"shown":[136],"bring":[138],"about":[139],"substantial":[140],"speedups.":[141],"MOSAIC\u2019s":[142],"superiority":[143],"achieving":[145],"desired":[147],"characteristics":[148],"subset":[152],"all":[153],"at":[154],"once":[155],"while":[156],"exhibiting":[157],"remarkable":[158],"robustness":[159],"various":[161],"outlier":[162],"types":[163],"is":[164],"demonstrated":[165],"via":[166],"extensive":[167],"experiments":[168],"conducted":[169],"both":[171],"real":[172],"synthetic":[174],"with":[176],"comparisons":[177],"state-of-the-art":[179],"algorithms.":[180]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}