{"id":"https://openalex.org/W4402193272","doi":"https://doi.org/10.1145/3670474.3685970","title":"Machine Learning VLSI CAD Experiments Should Consider Atomic Data Groups","display_name":"Machine Learning VLSI CAD Experiments Should Consider Atomic Data Groups","publication_year":2024,"publication_date":"2024-09-03","ids":{"openalex":"https://openalex.org/W4402193272","doi":"https://doi.org/10.1145/3670474.3685970"},"language":"en","primary_location":{"id":"doi:10.1145/3670474.3685970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3670474.3685970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD","raw_type":"proceedings-article"},"type":"conference-paper","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/A5057765982","display_name":"Andrew David Gunter","orcid":"https://orcid.org/0000-0003-2541-5125"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Andrew David Gunter","raw_affiliation_strings":["The University of British Columbia, Vancouver, British Columbia, Canada"],"raw_orcid":"https://orcid.org/0000-0003-2541-5125","affiliations":[{"raw_affiliation_string":"The University of British Columbia, Vancouver, British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013246362","display_name":"Steven J. E. Wilton","orcid":"https://orcid.org/0000-0002-1241-6690"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Steven Wilton","raw_affiliation_strings":["The University of British Columbia, Vancouver, British Columbia, Canada"],"raw_orcid":"https://orcid.org/0000-0002-1241-6690","affiliations":[{"raw_affiliation_string":"The University of British Columbia, Vancouver, British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":0.3556,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53952589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9940000176429749,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9940000176429749,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9824000000953674,"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9606000185012817,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/very-large-scale-integration","display_name":"Very-large-scale integration","score":0.8233695030212402},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.7693217992782593},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6595486402511597},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.42155230045318604},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33903002738952637},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.2335919439792633},{"id":"https://openalex.org/keywords/engineering-drawing","display_name":"Engineering drawing","score":0.22753185033798218},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1364976465702057}],"concepts":[{"id":"https://openalex.org/C14580979","wikidata":"https://www.wikidata.org/wiki/Q876049","display_name":"Very-large-scale integration","level":2,"score":0.8233695030212402},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.7693217992782593},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6595486402511597},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.42155230045318604},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33903002738952637},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2335919439792633},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.22753185033798218},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1364976465702057}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3670474.3685970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3670474.3685970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2005602803","https://openalex.org/W2023428606","https://openalex.org/W2899885603","https://openalex.org/W2997591727","https://openalex.org/W2999309192","https://openalex.org/W3011190810","https://openalex.org/W3033033241","https://openalex.org/W3162883552","https://openalex.org/W3182706339","https://openalex.org/W3206505512","https://openalex.org/W3210573375","https://openalex.org/W3214916413","https://openalex.org/W4238447347","https://openalex.org/W4297983978","https://openalex.org/W4297983986","https://openalex.org/W4383749600"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2334610590","https://openalex.org/W2320366403","https://openalex.org/W3204197061","https://openalex.org/W4251350712","https://openalex.org/W2134640991","https://openalex.org/W3027318491","https://openalex.org/W101478184","https://openalex.org/W1986774039"],"abstract_inverted_index":{"Machine":[0],"learning":[1],"(ML)":[2],"has":[3],"proved":[4],"useful":[5],"across":[6],"a":[7,51,95],"wide":[8],"range":[9],"of":[10,60,87,98,139],"applications":[11],"in":[12,76,91,110,116],"the":[13,84],"very-large-scale":[14],"integration":[15],"computer-aided":[16],"design":[17,93],"(VLSI":[18],"CAD)":[19],"domain.":[20],"To":[21],"avoid":[22,37],"overestimating":[23],"ML":[24,43,133],"models'":[25],"generalization":[26],"capabilities":[27],"for":[28,75],"real-world":[29],"deployments,":[30],"best":[31],"practices":[32],"utilize":[33],"realistic":[34],"data":[35,55,64,89,122,147],"and":[36,143],"test":[38],"set":[39],"information":[40],"leakage":[41],"during":[42,79],"model":[44,80,108,153],"preparation.":[45],"In":[46],"this":[47,117],"paper":[48],"we":[49],"identify":[50,144],"further":[52],"consideration,":[53],"atomic":[54,88,121,146],"groups,":[56],"which":[57],"are":[58,124,149],"sets":[59],"very":[61],"highly":[62],"correlated":[63],"that":[65,107,128],"may":[66],"also":[67],"lead":[68],"to":[69,136,151],"such":[70],"overestimation":[71],"if":[72],"not":[73],"accounted":[74],"train-test":[77,141],"splits":[78,142],"evaluation.":[81],"We":[82,126],"investigate":[83],"potential":[85],"impact":[86],"groups":[90,123,148],"experimental":[92],"through":[94],"case":[96,118],"study":[97,119],"field-programmable":[99],"gate":[100],"array":[101],"(FPGA)":[102],"routing.":[103],"Our":[104],"investigations":[105],"show":[106],"performance":[109],"deployment":[111],"is":[112],"overestimated":[113],"by":[114],"38%":[115],"when":[120,145],"ignored.":[125],"hope":[127],"these":[129],"results":[130],"motivate":[131],"other":[132],"CAD":[134],"practitioners":[135],"be":[137],"critical":[138],"their":[140,152],"relevant":[150],"evaluations.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
