{"id":"https://openalex.org/W2158677029","doi":"https://doi.org/10.1145/1390156.1390235","title":"A reproducing kernel Hilbert space framework for pairwise time series distances","display_name":"A reproducing kernel Hilbert space framework for pairwise time series distances","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2158677029","doi":"https://doi.org/10.1145/1390156.1390235","mag":"2158677029"},"language":"en","primary_location":{"id":"doi:10.1145/1390156.1390235","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1390156.1390235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th international conference on Machine learning - ICML '08","raw_type":"proceedings-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/A5084830556","display_name":"Zhengdong Lu","orcid":"https://orcid.org/0000-0002-6418-6030"},"institutions":[{"id":"https://openalex.org/I165690674","display_name":"Oregon Health & Science University","ror":"https://ror.org/009avj582","country_code":"US","type":"education","lineage":["https://openalex.org/I165690674"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhengdong Lu","raw_affiliation_strings":["Oregon Health & Science University, Beaverton, OR"],"affiliations":[{"raw_affiliation_string":"Oregon Health & Science University, Beaverton, OR","institution_ids":["https://openalex.org/I165690674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110201639","display_name":"Todd K. Leen","orcid":null},"institutions":[{"id":"https://openalex.org/I165690674","display_name":"Oregon Health & Science University","ror":"https://ror.org/009avj582","country_code":"US","type":"education","lineage":["https://openalex.org/I165690674"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Todd K. Leen","raw_affiliation_strings":["Oregon Health & Science University, Beaverton, OR"],"affiliations":[{"raw_affiliation_string":"Oregon Health & Science University, Beaverton, OR","institution_ids":["https://openalex.org/I165690674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103216219","display_name":"Yonghong Huang","orcid":"https://orcid.org/0000-0002-7706-5262"},"institutions":[{"id":"https://openalex.org/I165690674","display_name":"Oregon Health & Science University","ror":"https://ror.org/009avj582","country_code":"US","type":"education","lineage":["https://openalex.org/I165690674"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yonghong Huang","raw_affiliation_strings":["Oregon Health & Science University, Beaverton, OR"],"affiliations":[{"raw_affiliation_string":"Oregon Health & Science University, Beaverton, OR","institution_ids":["https://openalex.org/I165690674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083261801","display_name":"Deniz Erdo\u011fmu\u015f","orcid":"https://orcid.org/0000-0002-1114-3539"},"institutions":[{"id":"https://openalex.org/I165690674","display_name":"Oregon Health & Science University","ror":"https://ror.org/009avj582","country_code":"US","type":"education","lineage":["https://openalex.org/I165690674"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deniz Erdogmus","raw_affiliation_strings":["Oregon Health & Science University, Beaverton, OR"],"affiliations":[{"raw_affiliation_string":"Oregon Health & Science University, Beaverton, OR","institution_ids":["https://openalex.org/I165690674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5084830556"],"corresponding_institution_ids":["https://openalex.org/I165690674"],"apc_list":null,"apc_paid":null,"fwci":2.6588,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.90703583,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"624","last_page":"631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.998199999332428,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.998199999332428,"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/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9947999715805054,"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/reproducing-kernel-hilbert-space","display_name":"Reproducing kernel Hilbert space","score":0.7756662368774414},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7562545537948608},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7099080681800842},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.7018757462501526},{"id":"https://openalex.org/keywords/hilbert-space","display_name":"Hilbert space","score":0.593347430229187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5427127480506897},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4105425477027893},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.387955904006958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3273177444934845},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.16817128658294678},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.15256363153457642},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06909817457199097}],"concepts":[{"id":"https://openalex.org/C80884492","wikidata":"https://www.wikidata.org/wiki/Q3345678","display_name":"Reproducing kernel Hilbert space","level":3,"score":0.7756662368774414},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7562545537948608},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7099080681800842},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7018757462501526},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.593347430229187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5427127480506897},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4105425477027893},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.387955904006958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3273177444934845},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.16817128658294678},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.15256363153457642},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06909817457199097},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1390156.1390235","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1390156.1390235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th international conference on Machine learning - ICML '08","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.149.8347","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.8347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://icml2008.cs.helsinki.fi/papers/318.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.151.9400","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.151.9400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.ogi.edu/~tleen/Publications/luLeenICML08.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320307102","display_name":"Intel Corporation","ror":"https://ror.org/01ek73717"},{"id":"https://openalex.org/F4320309233","display_name":"Oregon Health and Science University","ror":"https://ror.org/009avj582"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W163215356","https://openalex.org/W1544068237","https://openalex.org/W1746819321","https://openalex.org/W1963551385","https://openalex.org/W2036732840","https://openalex.org/W2068403279","https://openalex.org/W2090840528","https://openalex.org/W2096765209","https://openalex.org/W2100599367","https://openalex.org/W2101005720","https://openalex.org/W2129106694","https://openalex.org/W2135001774","https://openalex.org/W2135624048","https://openalex.org/W2137037182","https://openalex.org/W2139212933","https://openalex.org/W2144068644","https://openalex.org/W2145295623","https://openalex.org/W2145851982","https://openalex.org/W2153675946","https://openalex.org/W2569586013","https://openalex.org/W3193477162"],"related_works":["https://openalex.org/W2065805792","https://openalex.org/W4285290579","https://openalex.org/W149320920","https://openalex.org/W3125885229","https://openalex.org/W4234882900","https://openalex.org/W1527525543","https://openalex.org/W2370512383","https://openalex.org/W2896570485","https://openalex.org/W1835315728","https://openalex.org/W2962818398"],"abstract_inverted_index":{"A":[0],"good":[1],"distance":[2,29,67,111,121],"measure":[3,30,112],"for":[4],"time":[5,49,69,89],"series":[6,50,70,90],"needs":[7],"to":[8,18,35,78,114],"properly":[9],"incorporate":[10],"the":[11,36,40,66,80,109,119],"temporal":[12],"structure,":[13],"and":[14,63],"should":[15],"be":[16],"applicable":[17],"sequences":[19],"with":[20,51,91],"unequal":[21],"lengths.":[22],"In":[23],"this":[24,83],"paper,":[25],"we":[26,76],"propose":[27,77],"a":[28,32,52,57,86],"as":[31],"principled":[33],"solution":[34],"two":[37,102],"requirements.":[38],"Unlike":[39],"conventional":[41,120],"feature":[42],"vector":[43],"representation,":[44],"our":[45],"approach":[46],"represents":[47],"each":[48],"summarizing":[53],"smooth":[54],"curve":[55],"in":[56],"reproducing":[58],"kernel":[59,81],"Hilbert":[60],"space":[61],"(RKHS),":[62],"therefore":[64],"translate":[65],"between":[68,73],"into":[71],"distances":[72],"curves.":[74],"Moreover":[75],"learn":[79],"of":[82,88],"RKHS":[84],"from":[85],"population":[87],"discrete":[92],"observations":[93],"using":[94],"Gaussian":[95],"process-based":[96],"non-parametric":[97],"mixed-effect":[98],"models.":[99],"Experiments":[100],"on":[101],"vastly":[103],"different":[104],"real-world":[105],"problems":[106],"show":[107],"that":[108],"proposed":[110],"leads":[113],"improved":[115],"classification":[116],"accuracy":[117],"over":[118],"measures.":[122],"1.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
