{"id":"https://openalex.org/W3166532787","doi":"https://doi.org/10.1051/epjconf/202125103036","title":"Event Classification with Multi-step Machine Learning","display_name":"Event Classification with Multi-step Machine Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3166532787","doi":"https://doi.org/10.1051/epjconf/202125103036","mag":"3166532787"},"language":"en","primary_location":{"id":"doi:10.1051/epjconf/202125103036","doi":"https://doi.org/10.1051/epjconf/202125103036","is_oa":true,"landing_page_url":"https://doi.org/10.1051/epjconf/202125103036","pdf_url":"https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03036.pdf","source":{"id":"https://openalex.org/S19068271","display_name":"EPJ Web of Conferences","issn_l":"2100-014X","issn":["2100-014X","2101-6275"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319748","host_organization_name":"EDP Sciences","host_organization_lineage":["https://openalex.org/P4310319748","https://openalex.org/P4310319982"],"host_organization_lineage_names":["EDP Sciences","Science Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Web of Conferences","raw_type":"journal-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03036.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087156611","display_name":"M. Saito","orcid":"https://orcid.org/0000-0001-5564-0935","observed_orcids":["https://orcid.org/0000-0001-5564-0935"]},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiko Saito","raw_affiliation_strings":["Institute for AI and Beyond, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for AI and Beyond, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tomoe Kishimoto","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoe Kishimoto","raw_affiliation_strings":["Institute for AI and Beyond, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for AI and Beyond, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuya Kaneta","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuya Kaneta","raw_affiliation_strings":["BrainPad Inc., 3-2-10 Shirokanedai, Minato, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BrainPad Inc., 3-2-10 Shirokanedai, Minato, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Taichi Itoh","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taichi Itoh","raw_affiliation_strings":["BrainPad Inc., 3-2-10 Shirokanedai, Minato, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BrainPad Inc., 3-2-10 Shirokanedai, Minato, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yoshiaki Umeda","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoshiaki Umeda","raw_affiliation_strings":["BrainPad Inc., 3-2-10 Shirokanedai, Minato, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BrainPad Inc., 3-2-10 Shirokanedai, Minato, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Junichi Tanaka","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junichi Tanaka","raw_affiliation_strings":["Institute for AI and Beyond, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for AI and Beyond, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112266112","display_name":"Y. Iiyama","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaro Iiyama","raw_affiliation_strings":["International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114374475","display_name":"R. Sawada","orcid":"https://orcid.org/0000-0002-2226-9874","observed_orcids":["https://orcid.org/0000-0002-2226-9874"]},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryu Sawada","raw_affiliation_strings":["International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056675059","display_name":"Koji Terashi","orcid":"https://orcid.org/0000-0001-6520-8070","observed_orcids":["https://orcid.org/0000-0001-6520-8070","https://orcid.org/0009-0003-7413-3535"]},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Terashi","raw_affiliation_strings":["International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International Center for Elementary Particle Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0818,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.29167804,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"251","issue":null,"first_page":"03036","last_page":"03036"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4336000084877014,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4336000084877014,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.3752000033855438,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.05689999833703041,"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/event-classification","display_name":"event classification","score":0.8849999904632568},{"id":"https://openalex.org/keywords/neural-architecture-search","display_name":"neural architecture search","score":0.8180000185966492},{"id":"https://openalex.org/keywords/double-asteroid-redirection-test","display_name":"DART","score":0.9269999861717224},{"id":"https://openalex.org/keywords/model-selection","display_name":"model selection","score":0.8529999852180481},{"id":"https://openalex.org/keywords/model-combination","display_name":"model combination","score":0.43299999833106995},{"id":"https://openalex.org/keywords/loss-function-design","display_name":"loss function design","score":0.7139999866485596}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7523999810218811},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7440999746322632},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6626999974250793},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6251000165939331},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6154999732971191},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.5590000152587891},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5496000051498413},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5407999753952026},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4984000027179718},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4627000093460083},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.4472000002861023},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.38530001044273376},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.33230000734329224},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.27970001101493835},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2551000118255615}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1051/epjconf/202125103036","doi":"https://doi.org/10.1051/epjconf/202125103036","is_oa":true,"landing_page_url":"https://doi.org/10.1051/epjconf/202125103036","pdf_url":"https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03036.pdf","source":{"id":"https://openalex.org/S19068271","display_name":"EPJ Web of Conferences","issn_l":"2100-014X","issn":["2100-014X","2101-6275"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319748","host_organization_name":"EDP Sciences","host_organization_lineage":["https://openalex.org/P4310319748","https://openalex.org/P4310319982"],"host_organization_lineage_names":["EDP Sciences","Science Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Web of Conferences","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2106.02301","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.02301","pdf_url":"https://arxiv.org/pdf/2106.02301","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:e9d3ef70f331496b9ce3fb875fb7edc2","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/e9d3ef70f331496b9ce3fb875fb7edc2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EPJ Web of Conferences, Vol 251, p 03036 (2021)","raw_type":"article"},{"id":"doi:10.48550/arxiv.2106.02301","doi":"https://doi.org/10.48550/arxiv.2106.02301","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2106.02301","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.1051/epjconf/202125103036","doi":"https://doi.org/10.1051/epjconf/202125103036","is_oa":true,"landing_page_url":"https://doi.org/10.1051/epjconf/202125103036","pdf_url":"https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03036.pdf","source":{"id":"https://openalex.org/S19068271","display_name":"EPJ Web of Conferences","issn_l":"2100-014X","issn":["2100-014X","2101-6275"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319748","host_organization_name":"EDP Sciences","host_organization_lineage":["https://openalex.org/P4310319748","https://openalex.org/P4310319982"],"host_organization_lineage_names":["EDP Sciences","Science Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Web of Conferences","raw_type":"journal-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G8382594990","display_name":"Development of experimental data analysis methods using deep learning for LHC and ATLAS","funder_award_id":"21K13936","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320313559","display_name":"CERN","ror":"https://ror.org/01ggx4157"},{"id":"https://openalex.org/F4320322832","display_name":"University of Tokyo","ror":"https://ror.org/057zh3y96"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338381","display_name":"SLAC National Accelerator Laboratory","ror":"https://ror.org/05gzmn429"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3166532787.pdf","grobid_xml":"https://content.openalex.org/works/W3166532787.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1987435915","https://openalex.org/W2125102738","https://openalex.org/W2125621954","https://openalex.org/W2165960883","https://openalex.org/W2194775991","https://openalex.org/W2736941579","https://openalex.org/W2895387432","https://openalex.org/W2916245928","https://openalex.org/W2946547492","https://openalex.org/W2960010704","https://openalex.org/W2963430933","https://openalex.org/W2963677766","https://openalex.org/W2965658867","https://openalex.org/W2981748264","https://openalex.org/W3041731188","https://openalex.org/W3096533519","https://openalex.org/W4213308398","https://openalex.org/W6600002382","https://openalex.org/W6600219630","https://openalex.org/W6600669965","https://openalex.org/W6601337496","https://openalex.org/W6604144753","https://openalex.org/W6607459698"],"related_works":[],"abstract_inverted_index":{"The":[0,51],"usefulness":[1],"and":[2,41,86,111,116,137,144,158],"value":[3],"of":[4,53,97],"Multi-step":[5],"Machine":[6],"Learning":[7],"(ML),":[8],"where":[9,94],"a":[10,25,133],"task":[11],"is":[12,34,44,100],"organized":[13],"into":[14],"connected":[15,40,49],"sub-tasks":[16],"with":[17,151],"known":[18],"intermediate":[19,32],"inference":[20],"goals,":[21],"as":[22,113,118,120,155],"opposed":[23],"to":[24,102],"single":[26],"large":[27],"model":[28,56,61,142],"learned":[29],"end-to-end":[30],"without":[31],"sub-tasks,":[33],"presented.":[35],"Pre-optimized":[36],"ML":[37,55,60,105],"models":[38,106,148],"are":[39,92,149,161],"better":[42],"performance":[43],"obtained":[45],"by":[46,69],"re-optimizing":[47],"the":[48,71,95,121,146],"one.":[50],"selection":[52,117],"an":[54,114],"from":[57],"several":[58],"small":[59],"candidates":[62],"for":[63,123],"each":[64],"sub-task":[65],"has":[66],"been":[67],"performed":[68],"using":[70],"idea":[72],"based":[73],"on":[74],"Neural":[75],"Architecture":[76,83],"Search":[77,84],"(NAS).":[78],"In":[79],"this":[80],"paper,":[81],"Differentiable":[82],"(DARTS)":[85],"Single":[87],"Path":[88],"One-Shot":[89],"NAS":[90],"(SPOS-NAS)":[91],"tested,":[93],"construction":[96],"loss":[98],"functions":[99],"improved":[101],"keep":[103],"all":[104],"smoothly":[107],"learning.":[108],"Using":[109],"DARTS":[110],"SPOS-NAS":[112],"optimization":[115],"well":[119,162],"connections":[122],"multi-step":[124],"machine":[125],"learning":[126],"systems,":[127],"we":[128],"find":[129],"that":[130],"(1)":[131],"such":[132,154],"system":[134],"can":[135],"quickly":[136],"successfully":[138],"select":[139],"highly":[140],"performant":[141],"combinations,":[143],"(2)":[145],"selected":[147],"consistent":[150],"baseline":[152],"algorithms,":[153],"grid":[156],"search,":[157],"their":[159],"outputs":[160],"controlled.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2021-06-22T00:00:00"}
