{"id":"https://openalex.org/W4403582897","doi":"https://doi.org/10.1145/3627673.3679891","title":"COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classification","display_name":"COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classification","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403582897","doi":"https://doi.org/10.1145/3627673.3679891"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679891","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679891","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679891","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679891","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077202036","display_name":"Jesus Barreda","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jesus Barreda","raw_affiliation_strings":["University of Texas Rio Grande Valley, Edinburg, TX, USA"],"raw_orcid":"https://orcid.org/0009-0009-5613-6920","affiliations":[{"raw_affiliation_string":"University of Texas Rio Grande Valley, Edinburg, TX, USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ashley Gomez","orcid":"https://orcid.org/0009-0005-1367-4690"},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashley Gomez","raw_affiliation_strings":["University of Texas Rio Grande Valley, Edinburg, TX, USA"],"raw_orcid":"https://orcid.org/0009-0005-1367-4690","affiliations":[{"raw_affiliation_string":"University of Texas Rio Grande Valley, Edinburg, TX, USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057626884","display_name":"Rub\u00e9n Puga","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruben Puga","raw_affiliation_strings":["University of Texas Rio Grande Valley, Edinburg, TX, USA"],"raw_orcid":"https://orcid.org/0009-0000-2865-977X","affiliations":[{"raw_affiliation_string":"University of Texas Rio Grande Valley, Edinburg, TX, USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071607114","display_name":"Kaixiong Zhou","orcid":"https://orcid.org/0000-0001-5226-8736"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaixiong Zhou","raw_affiliation_strings":["North Carolina State University, Raleigh, NC, USA"],"raw_orcid":"https://orcid.org/0000-0001-5226-8736","affiliations":[{"raw_affiliation_string":"North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000461117","display_name":"Li Zhang","orcid":"https://orcid.org/0000-0003-3665-3989"},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["University of Texas Rio Grande Valley, Edinburg, TX, USA"],"raw_orcid":"https://orcid.org/0000-0003-3665-3989","affiliations":[{"raw_affiliation_string":"University of Texas Rio Grande Valley, Edinburg, TX, USA","institution_ids":["https://openalex.org/I2802326326"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3622","last_page":"3626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"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/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9577000141143799,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7872517108917236},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7534811496734619},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.702791690826416},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6703211069107056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6061795353889465},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.5241377949714661},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5172872543334961},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46604740619659424},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44051581621170044},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4200851321220398},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4137907922267914},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06821030378341675},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.061250925064086914},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.04489034414291382},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.03910130262374878}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7872517108917236},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7534811496734619},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.702791690826416},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6703211069107056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6061795353889465},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.5241377949714661},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5172872543334961},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46604740619659424},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44051581621170044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4200851321220398},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4137907922267914},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06821030378341675},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.061250925064086914},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.04489034414291382},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.03910130262374878},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3627673.3679891","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679891","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679891","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2409.09645","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.09645","pdf_url":"https://arxiv.org/pdf/2409.09645","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:scholarworks.utrgv.edu:cs_fac-1194","is_oa":true,"landing_page_url":"https://scholarworks.utrgv.edu/cs_fac/195","pdf_url":"https://arxiv.org/pdf/2409.09645","source":{"id":"https://openalex.org/S4306402611","display_name":"ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2802326326","host_organization_name":"The University of Texas Rio Grande Valley","host_organization_lineage":["https://openalex.org/I2802326326"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science Faculty Publications and Presentations","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3627673.3679891","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679891","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679891","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4403582897.pdf"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2049877533","https://openalex.org/W2194775991","https://openalex.org/W2888477829","https://openalex.org/W2982438846","https://openalex.org/W2988244882","https://openalex.org/W2998010409","https://openalex.org/W3042807565","https://openalex.org/W3094624443","https://openalex.org/W3112330479","https://openalex.org/W3115948762","https://openalex.org/W3173748501","https://openalex.org/W3178159063","https://openalex.org/W3190461479","https://openalex.org/W4225537005","https://openalex.org/W4225856949","https://openalex.org/W4280565282","https://openalex.org/W4365393071"],"related_works":["https://openalex.org/W2497720472","https://openalex.org/W4292659306","https://openalex.org/W3044321615","https://openalex.org/W2806221744","https://openalex.org/W2326937258","https://openalex.org/W394267150","https://openalex.org/W2773965352","https://openalex.org/W4294892107","https://openalex.org/W2357748469","https://openalex.org/W2392917037"],"abstract_inverted_index":{"Multivariate":[0],"time":[1,23,116],"series":[2,24,117],"classification":[3,118],"is":[4,137],"an":[5,79],"important":[6],"task":[7],"with":[8],"widespread":[9],"domains":[10],"of":[11,48,96,112],"applications.":[12],"Recently,":[13],"deep":[14],"neural":[15],"networks":[16],"(DNN)":[17],"have":[18],"achieved":[19],"state-of-the-art":[20],"performance":[21],"in":[22,38,54,62],"classification.":[25],"However,":[26],"they":[27],"often":[28],"require":[29],"large":[30],"expert-labeled":[31],"training":[32,55],"datasets":[33],"which":[34],"can":[35],"be":[36],"infeasible":[37],"practice.":[39],"In":[40,69],"few-shot":[41,121],"settings,":[42],"i.e.":[43],"only":[44],"a":[45,59,82,89,97,103],"limited":[46],"number":[47],"samples":[49],"per":[50],"class":[51],"are":[52],"available":[53,138],"data,":[56],"DNNs":[57],"show":[58],"significant":[60],"drop":[61],"testing":[63],"accuracy":[64],"and":[65,81,102],"poor":[66],"generalization":[67,110],"ability.":[68],"this":[70],"paper,":[71],"we":[72,87],"propose":[73,88],"to":[74,107],"address":[75],"these":[76],"problems":[77,119],"from":[78],"optimization":[80,101],"loss":[83,105],"function":[84,106],"perspective.":[85],"Specifically,":[86],"new":[90],"learning":[91],"framework":[92],"named":[93],"COSCO":[94],"consisting":[95],"sharpness-aware":[98],"minimization":[99],"(SAM)":[100],"Prototypical":[104],"improve":[108],"the":[109,130],"ability":[111],"DNN":[113],"for":[114],"multivariate":[115],"under":[120],"setting.":[122],"Our":[123,134],"experiments":[124],"demonstrate":[125],"our":[126],"proposed":[127],"method":[128],"outperforms":[129],"existing":[131],"baseline":[132],"methods.":[133],"source":[135],"code":[136],"at:":[139],"https://github.com/JRB9/COSCO.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2024-10-21T00:00:00"}
