{"id":"https://openalex.org/W7154574983","doi":"https://doi.org/10.14428/esann/2026.es2026-335","title":"Multi-Scale Stochastic Neighbor Embedding with Twice Adaptive Bandwidths","display_name":"Multi-Scale Stochastic Neighbor Embedding with Twice Adaptive Bandwidths","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7154574983","doi":"https://doi.org/10.14428/esann/2026.es2026-335"},"language":null,"primary_location":{"id":"doi:10.14428/esann/2026.es2026-335","is_oa":true,"landing_page_url":"https://doi.org/10.14428/esann/2026.es2026-335","pdf_url":"https://doi.org/10.14428/esann/2026.es2026-335","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2026 proceesdings","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.14428/esann/2026.es2026-335","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103861190","display_name":"Lee John","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee John","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027485479","display_name":"Pierre Lambert","orcid":"https://orcid.org/0000-0001-7604-0584"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pierre Lambert","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092891786","display_name":"Edouard Couplet","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Edouard Couplet","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012308581","display_name":"P Merveille","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pierre Merveille","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067144586","display_name":"Dounia Mulders","orcid":"https://orcid.org/0000-0003-4855-5331"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dounia Mulders","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070860957","display_name":"Cyril de Bodt","orcid":"https://orcid.org/0000-0003-2347-1756"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cyril de Bodt","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5009959388","display_name":"Michel Verleysen","orcid":"https://orcid.org/0000-0003-4366-6155"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michel Verleysen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56109556,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"613","last_page":"618"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.1851000040769577,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.1851000040769577,"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.04410000145435333,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.043299999088048935,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4341000020503998},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.36910000443458557},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.3000999987125397},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.2976999878883362},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.26579999923706055},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.265500009059906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5213000178337097},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43700000643730164},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4341000020503998},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.36910000443458557},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3573000133037567},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2976999878883362},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.265500009059906},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14428/esann/2026.es2026-335","is_oa":true,"landing_page_url":"https://doi.org/10.14428/esann/2026.es2026-335","pdf_url":"https://doi.org/10.14428/esann/2026.es2026-335","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2026 proceesdings","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.14428/esann/2026.es2026-335","is_oa":true,"landing_page_url":"https://doi.org/10.14428/esann/2026.es2026-335","pdf_url":"https://doi.org/10.14428/esann/2026.es2026-335","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ESANN 2026 proceesdings","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7154574983.pdf","grobid_xml":"https://content.openalex.org/works/W7154574983.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Neighbor":[0,140],"embedding":[1,18,48,55,141,180,243],"has":[2],"been":[3],"a":[4,67,79,293],"quantum":[5],"leap":[6],"in":[7,25,33,45,66,89,161,269,300],"nonlinear":[8,149],"dimensionality":[9],"reduction,":[10],"revolutionizing":[11],"the":[12,22,26,46,109,203,218,229,232,241,301,307],"way":[13,69],"data":[14,28,128,143,160,236,298],"can":[15,283],"be":[16],"visualized.Neighbor":[17],"typically":[19],"adapts":[20],"to":[21,62,93,118,169,202,220,259],"local":[23,125,210],"density":[24,299],"highdimensional":[27],"space":[29],"with":[30,134,250],"adaptive":[31,113],"bandwidths":[32,44,65,85,97,114],"entropic":[34,310],"affinities,":[35],"while":[36],"it":[37,61],"resolves":[38],"scale":[39],"indeterminacies":[40],"by":[41,59],"having":[42,72,270],"unit":[43],"low-dimensional":[47,302],"space.In":[49],"this":[50,130],"paper,":[51],"multi-scale":[52,80],"stochastic":[53,186],"neighbor":[54,179],"(Ms.SNE)":[56],"is":[57,132,216,292],"improved":[58],"allowing":[60],"adapt":[63],"lowdimensional":[64],"data-driven":[68],"instead":[70],"of":[71,159,178,205,213,231,235,290,295,297,309],"fixed":[73],"ones.In":[74],"practice,":[75],"Ms.SNE":[76],"goes":[77],"through":[78],"optimization":[81],"process;":[82],"coordinates":[83,102,105],"and":[84,103,126,156,194,208],"are":[86,98,106,199],"optimized":[87,99,107],"separately,":[88],"an":[90],"alternate":[91],"fashion,":[92],"avoid":[94],"interferences:":[95],"(i)":[96],"from":[100,306],"previous":[101],"(ii)":[104],"given":[108],"new":[110],"bandwidths.Experimentally,":[111],"twice":[112],"improve":[115],"Ms.SNE's":[116],"capability":[117],"preserve":[119],"neighborhoods":[120,215,271],"on":[121,137,239,272],"all":[122],"scales,":[123],"i.e.,":[124],"global":[127,233],"structure;":[129],"claim":[131],"supported":[133],"quantitative":[135],"results":[136,305],"several":[138],"benchmarks.":[139],"for":[142,154],"visualizationDimensionality":[144],"reduction":[145],"(DR)":[146],"[1]":[147],"yields":[148],"embeddings":[150],"[2]":[151],"that":[152],"allow":[153],"visualization":[155],"exploratory":[157],"analysis":[158],"many":[162],"domains,":[163],"such":[164],"as":[165],"computational":[166],"biology":[167],"[3],":[168],"cite":[170],"just":[171],"one":[172],"example.Modern":[173],"DR":[174],"involves":[175],"mostly":[176],"methods":[177,198,223],"(NE)":[181],"[4],":[182],"like":[183],"Student":[184],"t-distributed":[185],"NE":[187,291],"(t-SNE)":[188],"[5]":[189,262],"or":[190,253,263,276],"uniform":[191],"manifold":[192],"approximation":[193],"projection":[195],"(UMAP)":[196],"[6].These":[197],"very":[200],"robust":[201],"curse":[204],"dimensionalty":[206],"[7]":[207],"produce":[209],"embeddings;":[211],"sparsity":[212,225],"small-size":[214],"also":[217,227],"key":[219],"accelerate":[221],"these":[222],"[8,6,9,10].However,":[224],"might":[226],"cause":[228],"loss":[230],"structure":[234],"[11,6,12,10,2,13,14].This":[237],"depends":[238],"how":[240],"final":[242],"does":[244],"reminisce":[245],"[12]":[246],"about":[247],"its":[248],"initialization":[249],"PCA":[251],"[15]":[252],"Laplacian":[254],"eigenmaps":[255],"[16],":[256],"either":[257],"due":[258],"early":[260],"stopping":[261],"explicit":[264],"regularization":[265],"[13].Another":[266],"workaround":[267],"consists":[268],"two":[273],"[9,":[274],"10]":[275],"more":[277,285],"scales":[278],"[11],":[279],"even":[280],"though":[281],"acceleration":[282],"become":[284],"difficult.A":[286],"less":[287],"investigated":[288],"feature":[289],"form":[294],"uniformization":[296],"(LD)":[303],"embedding.It":[304],"use":[308],"affinities":[311]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-17T00:00:00"}
