{"id":"https://openalex.org/W2740590008","doi":"https://doi.org/10.24963/ijcai.2017/372","title":"See without looking: joint visualization of sensitive multi-site datasets","display_name":"See without looking: joint visualization of sensitive multi-site datasets","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2740590008","doi":"https://doi.org/10.24963/ijcai.2017/372","mag":"2740590008"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/372","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/372","pdf_url":"https://www.ijcai.org/proceedings/2017/0372.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0372.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069354524","display_name":"Debbrata K. Saha","orcid":"https://orcid.org/0000-0003-0754-7570"},"institutions":[{"id":"https://openalex.org/I1334567473","display_name":"Mind Research Network","ror":"https://ror.org/032cjfs80","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1334567473"]},{"id":"https://openalex.org/I169521973","display_name":"University of New Mexico","ror":"https://ror.org/05fs6jp91","country_code":"US","type":"education","lineage":["https://openalex.org/I169521973"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debbrata K. Saha","raw_affiliation_strings":["The Mind Research Network","University of New Mexico","The Mind Research Network; University of New Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Mind Research Network","institution_ids":["https://openalex.org/I1334567473"]},{"raw_affiliation_string":"University of New Mexico","institution_ids":[]},{"raw_affiliation_string":"The Mind Research Network; University of New Mexico","institution_ids":["https://openalex.org/I1334567473","https://openalex.org/I169521973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032850756","display_name":"Vince D. Calhoun","orcid":"https://orcid.org/0000-0001-9058-0747"},"institutions":[{"id":"https://openalex.org/I1334567473","display_name":"Mind Research Network","ror":"https://ror.org/032cjfs80","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1334567473"]},{"id":"https://openalex.org/I169521973","display_name":"University of New Mexico","ror":"https://ror.org/05fs6jp91","country_code":"US","type":"education","lineage":["https://openalex.org/I169521973"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vince D. Calhoun","raw_affiliation_strings":["The Mind Research Network","University of New Mexico","The Mind Research Network; University of New Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Mind Research Network","institution_ids":["https://openalex.org/I1334567473"]},{"raw_affiliation_string":"University of New Mexico","institution_ids":[]},{"raw_affiliation_string":"The Mind Research Network; University of New Mexico","institution_ids":["https://openalex.org/I1334567473","https://openalex.org/I169521973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022649723","display_name":"Sandeep Panta","orcid":"https://orcid.org/0000-0002-6183-9139"},"institutions":[{"id":"https://openalex.org/I1334567473","display_name":"Mind Research Network","ror":"https://ror.org/032cjfs80","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1334567473"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sandeep R. Panta","raw_affiliation_strings":["The Mind Research Network"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Mind Research Network","institution_ids":["https://openalex.org/I1334567473"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082230429","display_name":"Sergey Plis","orcid":"https://orcid.org/0000-0003-0040-0365"},"institutions":[{"id":"https://openalex.org/I1334567473","display_name":"Mind Research Network","ror":"https://ror.org/032cjfs80","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1334567473"]},{"id":"https://openalex.org/I169521973","display_name":"University of New Mexico","ror":"https://ror.org/05fs6jp91","country_code":"US","type":"education","lineage":["https://openalex.org/I169521973"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergey M. Plis","raw_affiliation_strings":["The Mind Research Network","University of New Mexico","The Mind Research Network; University of New Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Mind Research Network","institution_ids":["https://openalex.org/I1334567473"]},{"raw_affiliation_string":"University of New Mexico","institution_ids":[]},{"raw_affiliation_string":"The Mind Research Network; University of New Mexico","institution_ids":["https://openalex.org/I1334567473","https://openalex.org/I169521973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4632,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.81608608,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2672","last_page":"2678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9955000281333923,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8280272483825684},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7063305377960205},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6967935562133789},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6759672164916992},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5947970151901245},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.552202045917511},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5252087712287903},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4862448275089264},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.4529728293418884},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4391133189201355},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42328715324401855},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4218376576900482},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3405713140964508},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2071727216243744},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1732843816280365},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07962790131568909}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8280272483825684},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7063305377960205},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6967935562133789},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6759672164916992},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5947970151901245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.552202045917511},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5252087712287903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4862448275089264},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.4529728293418884},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4391133189201355},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42328715324401855},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4218376576900482},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3405713140964508},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2071727216243744},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1732843816280365},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07962790131568909},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2017/372","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/372","pdf_url":"https://www.ijcai.org/proceedings/2017/0372.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/372","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/372","pdf_url":"https://www.ijcai.org/proceedings/2017/0372.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2175972824","display_name":"RI: Small: Collaborative Research: Learning Causal Structure from Complex Time Series Data","funder_award_id":"1318759","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5490080374","display_name":null,"funder_award_id":"IIS-1318759","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6508858857","display_name":null,"funder_award_id":"R01DA040487","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2740590008.pdf","grobid_xml":"https://content.openalex.org/works/W2740590008.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W198244778","https://openalex.org/W1979070592","https://openalex.org/W2001141328","https://openalex.org/W2053186076","https://openalex.org/W2103018059","https://openalex.org/W2128349406","https://openalex.org/W2134312057","https://openalex.org/W2145642814","https://openalex.org/W2157444450","https://openalex.org/W2167868121","https://openalex.org/W2169507824","https://openalex.org/W2187089797","https://openalex.org/W2330892731","https://openalex.org/W2510768630"],"related_works":["https://openalex.org/W2013728941","https://openalex.org/W4225274103","https://openalex.org/W2154046714","https://openalex.org/W2579659702","https://openalex.org/W2189613078","https://openalex.org/W1574055964","https://openalex.org/W2923661510","https://openalex.org/W2542318691","https://openalex.org/W2547096368","https://openalex.org/W2586219255"],"abstract_inverted_index":{"Visualization":[0],"of":[1,42,55,123,134],"high":[2],"dimensional":[3],"large-scale":[4],"datasets":[5],"via":[6,120],"an":[7,144],"embedding":[8,154,167],"into":[9],"a":[10,14,109,184],"2D":[11],"map":[12],"is":[13,90,126],"powerful":[15],"exploration":[16],"tool":[17,112],"for":[18,33,46,164],"assessing":[19],"latent":[20],"structure":[21],"in":[22,98,117],"the":[23,50,78,85,88,94,158,166],"data":[24,96,151],"and":[25,77,169],"detecting":[26],"outliers.":[27],"There":[28],"are":[29,44],"many":[30],"methods":[31],"developed":[32],"this":[34,107,148],"task":[35],"but":[36],"most":[37],"assume":[38],"that":[39,113,136],"all":[40,53,93],"pairs":[41,54],"samples":[43,76,135],"available":[45],"common":[47],"computation.":[48],"Specifically,":[49],"distances":[51,79],"between":[52],"points":[56],"need":[57],"to":[58,91,146,172,175,183],"be":[59,81,138],"directly":[60],"computable.":[61],"In":[62,106],"contrast,":[63],"we":[64,161],"work":[65],"with":[66,188],"sensitive":[67],"neuroimaging":[68,186],"data,":[69],"when":[70],"local":[71,95,124],"sites":[72],"cannot":[73,80,137],"share":[74],"their":[75,103],"easily":[82],"computed":[83],"across":[84],"sites.":[86,105],"Yet,":[87],"desire":[89],"let":[92],"participate":[97],"collaborative":[99],"computation":[100],"without":[101],"leaving":[102],"respective":[104],"scenario,":[108],"quality":[110,168],"control":[111],"visualizes":[114],"decentralized":[115,150],"dataset":[116,160,187],"its":[118,176],"entirety":[119],"global":[121],"aggregation":[122],"computations":[125],"especially":[127],"important":[128],"as":[129],"it":[130],"would":[131],"allow":[132],"screening":[133],"evaluated":[139],"otherwise.":[140],"This":[141],"paper":[142],"introduces":[143],"algorithm":[145],"solve":[147],"problem:":[149],"stochastic":[152],"neighbor":[153],"(dSNE).":[155],"Based":[156],"on":[157],"MNIST":[159],"introduce":[162],"metrics":[163],"measuring":[165],"use":[170],"them":[171],"compare":[173],"dSNE":[174,182],"centralized":[177],"counterpart.":[178],"We":[179],"also":[180],"apply":[181],"multi-site":[185],"encouraging":[189],"results.":[190]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
