{"id":"https://openalex.org/W4408879521","doi":"https://doi.org/10.1145/3687998.3717055","title":"Reproducibility Report for ACM SIGMOD 2024 Paper: 'Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs'","display_name":"Reproducibility Report for ACM SIGMOD 2024 Paper: 'Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs'","publication_year":2025,"publication_date":"2025-03-21","ids":{"openalex":"https://openalex.org/W4408879521","doi":"https://doi.org/10.1145/3687998.3717055"},"language":"en","primary_location":{"id":"doi:10.1145/3687998.3717055","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3687998.3717055","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3687998.3717055","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Reproducibility Reports of the 2024 International Conference on Management of Data","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3687998.3717055","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037956012","display_name":"Yihao Liu","orcid":"https://orcid.org/0009-0004-4623-5240"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yihao Liu","raw_affiliation_strings":["Tsinghua University, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-4623-5240","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015563796","display_name":"Yuanhui Luo","orcid":"https://orcid.org/0009-0003-8361-6766"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanhui Luo","raw_affiliation_strings":["Renmin University of China, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-8361-6766","affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051718290","display_name":"Minguk Choi","orcid":"https://orcid.org/0009-0003-4030-9344"},"institutions":[{"id":"https://openalex.org/I89015989","display_name":"Dankook University","ror":"https://ror.org/058pdbn81","country_code":"KR","type":"education","lineage":["https://openalex.org/I89015989"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minguk Choi","raw_affiliation_strings":["Dankook University, Yongin, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0003-4030-9344","affiliations":[{"raw_affiliation_string":"Dankook University, Yongin, Republic of Korea","institution_ids":["https://openalex.org/I89015989"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037956012"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02449771,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.25360000133514404,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.25360000133514404,"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/T13398","display_name":"Data Analysis with R","score":0.23469999432563782,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.22269999980926514,"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":0.7982345819473267},{"id":"https://openalex.org/keywords/reproducibility","display_name":"Reproducibility","score":0.6028541326522827},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3270261585712433},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19840079545974731},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10775560140609741}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7982345819473267},{"id":"https://openalex.org/C9893847","wikidata":"https://www.wikidata.org/wiki/Q1425625","display_name":"Reproducibility","level":2,"score":0.6028541326522827},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3270261585712433},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19840079545974731},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10775560140609741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3687998.3717055","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3687998.3717055","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3687998.3717055","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Reproducibility Reports of the 2024 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3687998.3717055","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3687998.3717055","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3687998.3717055","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Reproducibility Reports of the 2024 International Conference on Management of Data","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408879521.pdf"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W4399156126"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2413717610","https://openalex.org/W1973270181","https://openalex.org/W2417696084","https://openalex.org/W2368782778","https://openalex.org/W2087830269","https://openalex.org/W3106281778","https://openalex.org/W4324138256"],"abstract_inverted_index":{"In":[0],"general,":[1],"most":[2],"of":[3],"the":[4,8],"main":[5],"experiments":[6],"in":[7],"paper":[9],"''Can":[10],"Learned":[11],"Indexes":[12],"be":[13,23],"Built":[14],"Efficiently?":[15],"A":[16],"Deep":[17],"Dive":[18],"into":[19],"Sampling":[20],"Trade-offs''":[21],"can":[22],"successfully":[24],"reproduced.":[25]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}