{"id":"https://openalex.org/W4399428786","doi":"https://doi.org/10.1145/3665601.3669847","title":"SET: Searching Effective Supervised Learning Augmentations in Large Tabular Data Repositories","display_name":"SET: Searching Effective Supervised Learning Augmentations in Large Tabular Data Repositories","publication_year":2024,"publication_date":"2024-06-07","ids":{"openalex":"https://openalex.org/W4399428786","doi":"https://doi.org/10.1145/3665601.3669847"},"language":"en","primary_location":{"id":"doi:10.1145/3665601.3669847","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3665601.3669847","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3665601.3669847?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3665601.3669847?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048450551","display_name":"Jiaxiang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaxiang Liu","raw_affiliation_strings":["Columbia University, USA"],"raw_orcid":"https://orcid.org/0009-0009-5604-2027","affiliations":[{"raw_affiliation_string":"Columbia University, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002877429","display_name":"Zezhou Huang","orcid":"https://orcid.org/0009-0002-6613-0337"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zezhou Huang","raw_affiliation_strings":["Columbia University, USA"],"raw_orcid":"https://orcid.org/0009-0002-6613-0337","affiliations":[{"raw_affiliation_string":"Columbia University, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049016095","display_name":"Eugene Wu","orcid":"https://orcid.org/0000-0003-4254-6688"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eugene Wu","raw_affiliation_strings":["Columbia University, USA"],"raw_orcid":"https://orcid.org/0000-0003-4254-6688","affiliations":[{"raw_affiliation_string":"Columbia University, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"26","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11269","display_name":"Algorithms and Data Compression","score":0.9937000274658203,"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/computer-science","display_name":"Computer science","score":0.8214703798294067},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6404162645339966},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5207281708717346},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5035657286643982},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.47881370782852173},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.43111562728881836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3897046148777008},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3484548032283783},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.06730532646179199},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.05490812659263611}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8214703798294067},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6404162645339966},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5207281708717346},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5035657286643982},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.47881370782852173},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43111562728881836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3897046148777008},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3484548032283783},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.06730532646179199},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.05490812659263611}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3665601.3669847","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3665601.3669847","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3665601.3669847?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3665601.3669847","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3665601.3669847","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3665601.3669847?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1955634538","display_name":null,"funder_award_id":"1845638, 1740305, 2008295, 2106197, 2103794","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G2554194520","display_name":"Collaborative Research: CNS CORE: Medium: A Unified Prefetch Framework for Approximation Tolerant Interactive Applications","funder_award_id":"2106197","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2968948865","display_name":"CAREER: Visual Database Interfaces","funder_award_id":"1845638","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3486720790","display_name":"III: Small: Bringing database query optimization to data intensive applications","funder_award_id":"2008295","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5704097577","display_name":"Elements: Open-Source Cyberinfrastructure as a Decision Engine for Socioeconomic Disaster Risk (DESDR)","funder_award_id":"2103794","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6502487888","display_name":"SI2-SSE: Improving Scikit-Learn Usability and Automation","funder_award_id":"1740305","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399428786.pdf","grobid_xml":"https://content.openalex.org/works/W4399428786.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W2755087487","https://openalex.org/W2963560792","https://openalex.org/W3137081859","https://openalex.org/W3168854329","https://openalex.org/W3175808861","https://openalex.org/W4289533971","https://openalex.org/W6788106616"],"related_works":["https://openalex.org/W2027108423","https://openalex.org/W1855666948","https://openalex.org/W2758561209","https://openalex.org/W2786391746","https://openalex.org/W1548095260","https://openalex.org/W2594414941","https://openalex.org/W2781711915","https://openalex.org/W2112817590","https://openalex.org/W1555291398","https://openalex.org/W4381430104"],"abstract_inverted_index":{"Successful":[0],"supervised":[1,79],"learning":[2,80,121],"models":[3],"rely":[4],"on":[5],"predictive":[6,40],"features,":[7],"which":[8],"rarely":[9],"come":[10],"from":[11,42],"a":[12,16,78,85,101,110,148,157],"single":[13],"dataset.":[14],"As":[15],"result,":[17],"relevant":[18,43],"datasets":[19,44,89,155],"need":[20],"to":[21,113,122,136,145],"be":[22],"integrated":[23],"before":[24],"training":[25,125],"the":[26,54,57,67,93,96],"actual":[27],"model.":[28],"This":[29,51],"raises":[30],"one":[31,36],"natural":[32],"question:":[33],"\u201chow":[34],"can":[35],"efficiently":[37],"search":[38,60,68,146],"for":[39,45,84,147],"features":[41],"integration":[46],"with":[47,62,156],"responsible":[48],"AI":[49],"guarantees?\".":[50],"paper":[52],"formalizes":[53],"question":[55],"as":[56,109],"data":[58],"augmentation":[59,115,140,150],"problem":[61],"an":[63,73],"objective":[64],"of":[65,87,95,103,159],"minimizing":[66],"latency.":[69],"We":[70],"propose":[71],"SET,":[72],"interactive":[74],"system":[75,132],"that":[76,90],"intakes":[77],"task":[81],"and":[82,117,126,133],"searches":[83],"set":[86],"join-compatible":[88],"optimally":[91],"improve":[92],"performance":[94],"task.":[97],"Specifically,":[98],"SET":[99,130,144],"manages":[100],"corpus":[102],"relational":[104],"datasets,":[105],"uses":[106],"linear":[107],"regression":[108],"proxy":[111],"model":[112,124],"evaluate":[114],"candidates,":[116],"applies":[118],"factorized":[119],"machine":[120],"accelerate":[123],"evaluation":[127],"algorithmically.":[128],"Furthermore,":[129],"leverages":[131],"hardware":[134],"optimizations":[135],"maximize":[137],"parallelism":[138],"across":[139],"searches.":[141],"These":[142],"allow":[143],"good":[149],"plan":[151],"over":[152],"1":[153],"million":[154],"latency":[158],"1.4":[160],"seconds.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}