{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T14:11:50Z","timestamp":1756995110590,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","award":["W911NF2110230"],"award-info":[{"award-number":["W911NF2110230"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["IIS-1552538, IIS-1703431, CCF-1750140, IIS-1814493, CCF-1955703, CCF-2007556, IIS-2008107"],"award-info":[{"award-number":["IIS-1552538, IIS-1703431, CCF-1750140, IIS-1814493, CCF-1955703, CCF-2007556, IIS-2008107"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH (National Institutes of Health)","doi-asserted-by":"publisher","award":["R01EB025021"],"award-info":[{"award-number":["R01EB025021"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,10]]},"DOI":"10.1145\/3514221.3517896","type":"proceedings-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T02:33:49Z","timestamp":1655001229000},"page":"959-972","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Selectivity Functions of Range Queries are Learnable"],"prefix":"10.1145","author":[{"given":"Xiao","family":"Hu","sequence":"first","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxi","family":"Liu","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haibo","family":"Xiu","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pankaj K.","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Debmalya","family":"Panigrahi","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sudeepa","family":"Roy","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Yang","sequence":"additional","affiliation":[{"name":"Duke University, Durham, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,6,11]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"P. K. Agarwal and M. Sharir. 2000. Arrangements and their applications. In Handbook of computational geometry. Elsevier 49--119."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/263867.263927"},{"key":"e_1_3_2_1_3_1","unstructured":"M. Anthony and P. L. Bartlett. 2009. Neural network learning: Theoretical foundations .cambridge university press."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/225298.225346"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1996.0033"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007447530834"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"N. Brisaboa O. Pedreira D. Seco R. Solar and R. Uribe. 2008. Clustering-based similarity search in metric spaces with sparse spatial centers. In SOFSEM. Springer 186--197.","DOI":"10.1007\/978-3-540-77566-9_16"},{"volume-title":"Proc. 20th ACM SIGMOD Int. Conf. Management Data. 211--222","author":"Bruno N.","key":"e_1_3_2_1_8_1","unstructured":"N. Bruno, S. Chaudhuri, and L. Gravano. 2001. STHoles: A multidimensional workload-aware histogram. In Proc. 20th ACM SIGMOD Int. Conf. Management Data. 211--222."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02187743"},{"key":"e_1_3_2_1_10_1","unstructured":"D. Dua and C. Graf. 2017. UCI machine learning repository. (2017). http:\/\/archive.ics.uci.edu\/ml\/index.php"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/3329772.3329780"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"W. R. Gilks S. Richardson and D. Spiegelhalter. 1995. Markov chain Monte Carlo in practice .CRC press.","DOI":"10.1201\/b14835"},{"volume-title":"Proc. 39th ACM SIGMOD Int. Conf. Management Data. 1035--1050","author":"Hasan S.","key":"e_1_3_2_1_13_1","unstructured":"S. Hasan, S. Thirumuruganathan, J. Augustine, N. Koudas, and G. Das. 2020. Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries. In Proc. 39th ACM SIGMOD Int. Conf. Management Data. 1035--1050."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/0890-5401(92)90010-D"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02187876"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.14778\/3384345.3384349"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687723"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-0000(05)80062-5"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"M. J. Kearns and U. Vazirani. 1994. An introduction to computational learning theory .MIT press.","DOI":"10.7551\/mitpress\/3897.001.0001"},{"key":"e_1_3_2_1_20_1","unstructured":"A. Kipf T. Kipf B. Radke V. Leis P. Boncz and A. Kemper. 2019. Learned cardinalities: Estimating correlated joins with deep learning. (2019)."},{"volume-title":"Proc. 9th ACM SIGMOD Int. Conf. Management Data. 1--11","author":"Lipton R. J.","key":"e_1_3_2_1_21_1","unstructured":"R. J. Lipton, J. F. Naughton, and D. A. Schneider. 1990. Practical selectivity estimation through adaptive sampling. In Proc. 9th ACM SIGMOD Int. Conf. Management Data. 1--11."},{"key":"e_1_3_2_1_22_1","volume-title":"Bao: Learning to Steer Query Optimizers. arXiv preprint arXiv:2004.03814","author":"Marcus R.","year":"2020","unstructured":"R. Marcus, P. Negi, H. Mao, N. Tatbul, M. Alizadeh, and T. Kraska. 2020. Bao: Learning to Steer Query Optimizers. arXiv preprint arXiv:2004.03814 (2020)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.14778\/3342263.3342644"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"R. Marcus and O. Papaemmanouil. 2018. Deep reinforcement learning for join order enumeration. In aiDM. 1--4.","DOI":"10.1145\/3211954.3211957"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-006-0030-1"},{"volume-title":"Proc. 31th Very Large Data Bases. 373--384","author":"Markl V.","key":"e_1_3_2_1_26_1","unstructured":"V. Markl, N. Megiddo, M. Kutsch, T. M. Tran, P. Haas, and U. Srivastava. 2005. Consistently estimating the selectivity of conjuncts of predicates. In Proc. 31th Very Large Data Bases. 373--384."},{"volume-title":"Proc. 17th ACM SIGMOD Int. Conf. Management Data. 448--459","author":"Matias Y.","key":"e_1_3_2_1_27_1","unstructured":"Y. Matias, J. S. Vitter, and M. Wang. 1998. Wavelet-based histograms for selectivity estimation. In Proc. 17th ACM SIGMOD Int. Conf. Management Data. 448--459."},{"key":"e_1_3_2_1_28_1","unstructured":"M. Mattig T. Fober C. Beilschmidt and B. Seeger. 2018. Kernel-Based Cardinality Estimation on Metric Data. In EDBT. 349--360."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687738"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"S. Muthukrishnan V. Poosala and T. Suel. 1999. On rectangular partitionings in two dimensions: Algorithms complexity and applications. In ICDT. Springer 236--256.","DOI":"10.1007\/3-540-49257-7_16"},{"volume-title":"Proc. 36th Annu. IEEE Int. Conf. Data Eng. IEEE, 154--157","author":"Negi P.","key":"e_1_3_2_1_31_1","unstructured":"P. Negi, R. Marcus, H. Mao, N. Tatbul, T. Kraska, and M. Alizadeh. 2020. Cost-Guided Cardinality Estimation: Focus Where it Matters. In Proc. 36th Annu. IEEE Int. Conf. Data Eng. IEEE, 154--157."},{"key":"e_1_3_2_1_32_1","unstructured":"J. Pach and P. K. Agarwal. 2011. Combinatorial geometry. Vol. 37. John Wiley & Sons."},{"volume-title":"Proc. 39th ACM SIGMOD Int. Conf. Management Data,. 1017--1033","author":"Park Y.","key":"e_1_3_2_1_33_1","unstructured":"Y. Park, S. Zhong, and B. Mozafari. 2020. Quicksel: Quick selectivity learning with mixture models. In Proc. 39th ACM SIGMOD Int. Conf. Management Data,. 1017--1033."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/235968.233342"},{"key":"e_1_3_2_1_35_1","volume-title":"VLDB","volume":"97","author":"Poosala V.","unstructured":"V. Poosala and Y. E. Ioannidis. 1997. Selectivity estimation without the attribute value independence assumption. In VLDB, Vol. 97. Citeseer, 486--495."},{"volume-title":"Proc. 22th Annu. IEEE Int. Conf. Data Eng. 39--39","author":"Srivastava U.","key":"e_1_3_2_1_36_1","unstructured":"U. Srivastava, P. J. Haas, V. Markl, M. Kutsch, and T. M. Tran. 2006. Isomer: Consistent histogram construction using query feedback. In Proc. 22th Annu. IEEE Int. Conf. Data Eng. 39--39."},{"volume-title":"Proc. 17th Int. Conf. World Wide Web. 595--604","author":"Stocker M.","key":"e_1_3_2_1_37_1","unstructured":"M. Stocker, A. Seaborne, A. Bernstein, C. Kiefer, and D. Reynolds. 2008. SPARQL basic graph pattern optimization using selectivity estimation. In Proc. 17th Int. Conf. World Wide Web. 595--604."},{"volume-title":"Proc. 40th ACM SIGMOD Int. Conf. Management Data .","author":"Sun J.","key":"e_1_3_2_1_38_1","unstructured":"J. Sun, G. Li, and N. Tang. 2021. Learned Cardinality Estimation for Similarity Queries. In Proc. 40th ACM SIGMOD Int. Conf. Management Data ."},{"key":"e_1_3_2_1_39_1","volume-title":"Proc. IEEE Melecon","volume":"83","author":"Toussaint G. T.","year":"1983","unstructured":"G. T. Toussaint. 1983. Solving geometric problems with the rotating calipers. In Proc. IEEE Melecon, Vol. 83. A10."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/1968.1972"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.5555\/211359"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"V. N. Vapnik and A. Y. Chervonenkis. 2015. On the uniform convergence of relative frequencies of events to their probabilities. In Measures of complexity. Springer 11--30.","DOI":"10.1007\/978-3-319-21852-6_3"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.14778\/3461535.3461552"},{"volume-title":"Proc. 39th ACM SIGMOD Int. Conf. Management Data. 1197--1212","author":"Wang Y.","key":"e_1_3_2_1_44_1","unstructured":"Y. Wang, C. Xiao, J. Qin, X. Cao, Y. Sun, W. Wang, and M. Onizuka. 2020. Monotonic cardinality estimation of similarity selection: A deep learning approach. In Proc. 39th ACM SIGMOD Int. Conf. Management Data. 1197--1212."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/0012-365X(81)90274-0"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.14778\/3368289.3368294"}],"event":{"name":"SIGMOD\/PODS '22: International Conference on Management of Data","sponsor":["SIGMOD ACM Special Interest Group on Management of Data"],"location":"Philadelphia PA USA","acronym":"SIGMOD\/PODS '22"},"container-title":["Proceedings of the 2022 International Conference on Management of Data"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514221.3517896","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3514221.3517896","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3514221.3517896","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:36Z","timestamp":1750188636000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514221.3517896"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,10]]},"references-count":46,"alternative-id":["10.1145\/3514221.3517896","10.1145\/3514221"],"URL":"https:\/\/doi.org\/10.1145\/3514221.3517896","relation":{},"subject":[],"published":{"date-parts":[[2022,6,10]]},"assertion":[{"value":"2022-06-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}