{"id":"https://openalex.org/W2039158811","doi":"https://doi.org/10.1109/icassp.2014.6854229","title":"Revisiting robustness of the union-of-subspaces model for data-adaptive learning of nonlinear signal models","display_name":"Revisiting robustness of the union-of-subspaces model for data-adaptive learning of nonlinear signal models","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2039158811","doi":"https://doi.org/10.1109/icassp.2014.6854229","mag":"2039158811"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6854229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101994751","display_name":"Tong Wu","orcid":"https://orcid.org/0000-0002-8935-1629"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tong Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The State University of New Jersey, Rutgers","Dept. of Electr. & Comput. Eng., Rutgers, State Univ. of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The State University of New Jersey, Rutgers","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Rutgers, State Univ. of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028718006","display_name":"Waheed U. Bajwa","orcid":"https://orcid.org/0000-0003-4406-5263"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Waheed U. Bajwa","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The State University of New Jersey, Rutgers","Dept. of Electr. & Comput. Eng., Rutgers, State Univ. of New Jersey, Piscataway, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The State University of New Jersey, Rutgers","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Rutgers, State Univ. of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102322142"],"apc_list":null,"apc_paid":null,"fwci":0.7454,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66722176,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"16","issue":null,"first_page":"3390","last_page":"3394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9976999759674072,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9975000023841858,"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/linear-subspace","display_name":"Linear subspace","score":0.8595141768455505},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8023868799209595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5500085949897766},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5209770798683167},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5104824304580688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47896650433540344},{"id":"https://openalex.org/keywords/data-driven","display_name":"Data-driven","score":0.43600916862487793},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2810431718826294},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07816746830940247},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.07142597436904907}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.8595141768455505},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8023868799209595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5500085949897766},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5209770798683167},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5104824304580688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47896650433540344},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.43600916862487793},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2810431718826294},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07816746830940247},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.07142597436904907},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp.2014.6854229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.638.990","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.638.990","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.rci.rutgers.edu/~wub1/pubs/icassp14_MCUoS.pdf","raw_type":"text"},{"id":"pmh:oai:alma.01RUT_INST:11665126130004646","is_oa":false,"landing_page_url":"https://scholarship.libraries.rutgers.edu/esploro/outputs/conferenceProceeding/Revisiting-robustness-of-the-union-of-subspaces-model/991031665796404646","pdf_url":null,"source":{"id":"https://openalex.org/S4210197018","display_name":"View","issn_l":"2688-268X","issn":["2688-268X","2688-3988"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1533128638","https://openalex.org/W1606778734","https://openalex.org/W1988219946","https://openalex.org/W1993962865","https://openalex.org/W2009234819","https://openalex.org/W2032986522","https://openalex.org/W2041861271","https://openalex.org/W2045512849","https://openalex.org/W2061375390","https://openalex.org/W2069912449","https://openalex.org/W2071128523","https://openalex.org/W2073849744","https://openalex.org/W2076428552","https://openalex.org/W2088844072","https://openalex.org/W2102628473","https://openalex.org/W2103943817","https://openalex.org/W2106589580","https://openalex.org/W2125742596","https://openalex.org/W2125874614","https://openalex.org/W2139054653","https://openalex.org/W2141820132","https://openalex.org/W2143168132","https://openalex.org/W2152714163","https://openalex.org/W2153663612","https://openalex.org/W2157529069","https://openalex.org/W2159268085","https://openalex.org/W2160547390","https://openalex.org/W2162991150","https://openalex.org/W2165916500","https://openalex.org/W2177347332","https://openalex.org/W2561426102","https://openalex.org/W2613579343","https://openalex.org/W2798766386","https://openalex.org/W2962834831","https://openalex.org/W3099880660","https://openalex.org/W3102566946","https://openalex.org/W4242209908","https://openalex.org/W4301495617","https://openalex.org/W6652584071","https://openalex.org/W6686567431"],"related_works":["https://openalex.org/W2391321755","https://openalex.org/W2896134808","https://openalex.org/W2949110394","https://openalex.org/W4211228991","https://openalex.org/W2353790329","https://openalex.org/W2754495451","https://openalex.org/W2279743781","https://openalex.org/W3019634500","https://openalex.org/W140666874","https://openalex.org/W1978233018"],"abstract_inverted_index":{"This":[0],"paper":[1],"revisits":[2],"the":[3,14,30,35,56,91],"problem":[4],"of":[5,8,29,52,58,85],"data-adaptive":[6,50],"learning":[7,51,70],"geometric":[9],"signal":[10],"structures":[11],"based":[12],"on":[13],"Union-of-Subspaces":[15,37],"(UoS)":[16],"model.":[17,39],"In":[18,40],"contrast":[19],"to":[20,69],"prior":[21],"work,":[22],"it":[23,43],"motivates":[24],"and":[25,60,79,90],"investigates":[26],"an":[27,53,87],"extension":[28],"classical":[31],"UoS":[32,72],"model,":[33],"termed":[34],"Metric-Constrained":[36],"(MC-UoS)":[38],"this":[41],"regard,":[42],"puts":[44],"forth":[45],"two":[46],"iterative":[47],"methods":[48,65],"for":[49],"MC-UoS":[54,88],"in":[55,73],"presence":[57],"complete":[59],"missing":[61],"data.":[62],"The":[63],"proposed":[64,92],"outperform":[66],"existing":[67],"approaches":[68],"a":[71],"numerical":[74],"experiments":[75],"involving":[76],"both":[77,86],"synthetic":[78],"real":[80],"data,":[81],"which":[82],"demonstrates":[83],"effectiveness":[84],"model":[89],"methods.":[93]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}