{"id":"https://openalex.org/W2556397940","doi":"https://doi.org/10.1109/mlsp.2016.7738831","title":"Data privacy protection by kernel subspace projection and generalized eigenvalue decomposition","display_name":"Data privacy protection by kernel subspace projection and generalized eigenvalue decomposition","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2556397940","doi":"https://doi.org/10.1109/mlsp.2016.7738831","mag":"2556397940"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2016.7738831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5047747213","display_name":"Konstantinos Diamantaras","orcid":"https://orcid.org/0000-0003-1373-4022"},"institutions":[{"id":"https://openalex.org/I77990126","display_name":"Alexander Technological Educational Institute of Thessaloniki","ror":"https://ror.org/04h36ea57","country_code":"GR","type":"education","lineage":["https://openalex.org/I77990126"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Konstantinos Diamantaras","raw_affiliation_strings":["TEI of Thessaloniki, Dept. Information Technology, Sindos, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TEI of Thessaloniki, Dept. Information Technology, Sindos, Greece","institution_ids":["https://openalex.org/I77990126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072714962","display_name":"Sun\u2010Yuan Kung","orcid":"https://orcid.org/0000-0002-7314-0720"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sun-Yuan Kung","raw_affiliation_strings":["Dept. Electrical Engineering, Princeton University, Princeton, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical Engineering, Princeton University, Princeton, NJ, USA","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7178,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.93077571,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.996999979019165,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.996999979019165,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9836000204086304,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9704999923706055,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7575154304504395},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5743901133537292},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5742271542549133},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5631259679794312},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4825717508792877},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.47829800844192505},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4725636839866638},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.4370112717151642},{"id":"https://openalex.org/keywords/information-sensitivity","display_name":"Information sensitivity","score":0.42800503969192505},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41552799940109253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35867393016815186},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3504398465156555},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34433579444885254},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3028505742549896},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.30141767859458923},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24664902687072754},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.21462133526802063},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1775316298007965}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7575154304504395},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5743901133537292},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5742271542549133},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5631259679794312},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4825717508792877},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.47829800844192505},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4725636839866638},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.4370112717151642},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.42800503969192505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41552799940109253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35867393016815186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3504398465156555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34433579444885254},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3028505742549896},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.30141767859458923},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24664902687072754},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.21462133526802063},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1775316298007965},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2016.7738831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2016.7738831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1850196515","https://openalex.org/W2046996006","https://openalex.org/W2140596092","https://openalex.org/W2150796457","https://openalex.org/W2151956781","https://openalex.org/W2155025398","https://openalex.org/W2160553465","https://openalex.org/W2277202671","https://openalex.org/W2799061466"],"related_works":["https://openalex.org/W155772811","https://openalex.org/W2135267219","https://openalex.org/W2905418897","https://openalex.org/W3033319502","https://openalex.org/W2129407254","https://openalex.org/W247270383","https://openalex.org/W2610521515","https://openalex.org/W2050029313","https://openalex.org/W1509134351","https://openalex.org/W2146516920"],"abstract_inverted_index":{"Various":[0],"internet":[1],"services,":[2],"including":[3],"cloud":[4],"providers":[5],"and":[6,57],"social":[7],"networks":[8],"collect":[9],"large":[10],"amounts":[11],"of":[12,51,115,118,129,156],"information":[13],"that":[14,96],"needs":[15],"to":[16],"be":[17,37],"processed":[18],"for":[19],"statistical":[20],"or":[21],"other":[22],"reasons":[23],"without":[24],"breaching":[25],"user":[26],"privacy.":[27],"We":[28,123],"present":[29],"a":[30,40,49,55,59,100,116,126],"novel":[31,101],"approach":[32,131],"where":[33],"privacy":[34,63],"protection":[35,64],"can":[36],"viewed":[38],"as":[39,48,91,93],"data":[41,147,153],"transformation":[42],"problem.":[43],"The":[44],"problem":[45],"is":[46,65,108,161,170],"formulated":[47],"pair":[50,117],"classification":[52,74],"tasks,":[53],"(a)":[54],"privacy-insensitive":[56],"(b)":[58],"privacy-sensitive":[60],"task.":[61],"Then":[62],"the":[66,70,80,85,88,111,133,143,150,154,157,166],"requirement":[67],"that,":[68],"given":[69],"transformed":[71],"data,":[72],"no":[73],"algorithm":[75],"may":[76],"perform":[77],"well":[78],"on":[79,87],"sensitive":[81],"task":[82,90,160,169],"while":[83,165],"hurting":[84],"performance":[86,155],"insensitive":[89],"little":[92],"possible.":[94],"To":[95],"end,":[97],"we":[98],"introduce":[99],"criterion":[102],"called":[103],"Multiclass":[104],"Discriminant":[105],"Ratio":[106],"which":[107],"optimized":[109],"using":[110,132,142],"generalized":[112],"eigenvalue":[113],"decomposition":[114],"between":[119],"class":[120],"scatter":[121],"matrices.":[122],"then":[124],"formulate":[125],"nonlinear":[127],"extension":[128],"this":[130],"kernel":[134,151],"GED":[135],"method.":[136],"Our":[137],"proposed":[138],"methods":[139],"are":[140],"evaluated":[141],"Human":[144],"Activity":[145,167],"Recognition":[146],"set.":[148],"Using":[149],"projected":[152],"User":[158],"recognition":[159,168],"reduced":[162,171],"by":[163,173],"89%":[164],"only":[172],"7.8%.":[174]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
