{"id":"https://openalex.org/W4416582603","doi":"https://doi.org/10.1109/tetci.2025.3631626","title":"ProtoNAS: Accelerating Differentiable Neural Architecture Search via Prototypical Data Pruning","display_name":"ProtoNAS: Accelerating Differentiable Neural Architecture Search via Prototypical Data Pruning","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W4416582603","doi":"https://doi.org/10.1109/tetci.2025.3631626"},"language":null,"primary_location":{"id":"doi:10.1109/tetci.2025.3631626","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3631626","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-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/A5084126009","display_name":"Liming Shi","orcid":"https://orcid.org/0000-0003-4129-0668"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liming Shi","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100894390","display_name":"Lan Deng","orcid":"https://orcid.org/0009-0002-4830-9544"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Deng","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005210294","display_name":"Gaochang Wu","orcid":"https://orcid.org/0000-0002-5149-2995"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaochang Wu","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100630363","display_name":"Jingxin Zhang","orcid":"https://orcid.org/0000-0002-9450-188X"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jingxin Zhang","raw_affiliation_strings":["School of Engineering, Swinburne University of Technology, Melbourne, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering, Swinburne University of Technology, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022740106","display_name":"Jinliang Ding","orcid":"https://orcid.org/0000-0003-3735-0672"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinliang Ding","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5084126009"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36969078,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"2","first_page":"1170","last_page":"1184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.3102000057697296,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.3102000057697296,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.21770000457763672,"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":0.1200999990105629,"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/pruning","display_name":"Pruning","score":0.8418999910354614},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5522000193595886},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5317999720573425},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.476500004529953},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.46700000762939453},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.4544000029563904},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.40709999203681946}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.8418999910354614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6966000199317932},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5522000193595886},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5317999720573425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5081999897956848},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.46700000762939453},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.4544000029563904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4174000024795532},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40950000286102295},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.2863999903202057},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27090001106262207}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2025.3631626","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2025.3631626","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,48,144],"take":[4],"a":[5,114,146,193,230],"close":[6],"look":[7],"at":[8,151],"the":[9,18,28,32,62,83,93,105,111,122,126,132,153,156,168,172,175],"efficient":[10],"differentiable":[11],"Neural":[12],"Architecture":[13],"Search":[14],"(NAS)":[15],"problem":[16],"through":[17],"lens":[19],"of":[20,65,128,174],"data":[21,54,67,88,225],"pruning.":[22],"A":[23],"key":[24],"insight":[25],"is":[26,163],"that":[27,57,90,189],"core":[29],"samples":[30],"in":[31,131],"pruned":[33],"dataset":[34],"can":[35,191],"be":[36],"interpreted":[37],"as":[38,214],"support":[39],"vectors":[40],"for":[41],"networks":[42],"to":[43,69,99,125,165,208,222],"make":[44],"informed":[45],"decisions.":[46],"Therefore,":[47],"introduce":[49,145],"ProtoNAS,":[50],"an":[51],"innovative":[52],"prototypical":[53,63,106],"pruning":[55,89,148,196,226],"method":[56],"dynamically":[58,79],"and":[59,95,116,184,210,216,236],"explicitly":[60],"measures":[61],"distance":[64,107,112],"each":[66],"sample":[68,115,142],"its":[70,117,211],"class-specific":[71,118],"clustering":[72],"centroid":[73],"(i.e.,":[74],"prototype).":[75],"These":[76],"prototypes":[77,127],"are":[78],"updated":[80],"on-the-fly":[81],"throughout":[82],"search":[84,186,234,237],"phase,":[85],"enabling":[86],"flexible":[87],"adjusts":[91],"with":[92,155,198],"architectures":[94],"network":[96],"parameters.":[97],"Compared":[98,221],"conventional":[100],"cross-entropy-based":[101],"or":[102,202],"Euclidean-based":[103],"distances,":[104],"not":[108],"only":[109],"considers":[110],"between":[113,233],"prototype,":[119],"but":[120],"also":[121],"relative":[123],"distances":[124],"other":[129],"classes":[130,154],"embedding":[133],"space,":[134],"facilitating":[135],"more":[136],"precise":[137],"score":[138],"assignment.":[139],"Furthermore,":[140],"beyond":[141],"pruning,":[143],"class":[147],"policy":[149,162],"aimed":[150],"masking":[152],"lowest":[157],"average":[158],"scores.":[159],"This":[160],"additional":[161],"designed":[164],"further":[166],"expedite":[167],"NAS":[169],"without":[170],"compromising":[171],"performance":[173,200,205,235],"final":[176],"searched":[177],"architecture.":[178],"Extensive":[179],"experiments":[180],"conducted":[181],"on":[182],"NAS-Bench-201":[183],"NAS-Bench-1Shot1":[185],"spaces":[187],"demonstrate":[188],"ProtoNAS":[190,228],"achieve":[192],"significant":[194],"90%":[195],"rate":[197],"minimal":[199],"trade-offs":[201],"even":[203],"improved":[204],"when":[206],"applied":[207],"DARTS":[209],"variants,":[212],"such":[213],"PC-DARTS":[215],"<inline-formula":[217],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[218],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[219],"notation=\"LaTeX\">$\\beta$</tex-math></inline-formula>-DARTS.":[220],"State-Of-The-Art":[223],"(SOTA)":[224],"techniques,":[227],"achieves":[229],"superior":[231],"balance":[232],"cost.":[238]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-25T00:00:00"}