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Estimating the selectivity of a query is a key step in almost any cost-based query optimizer.
Selectivity Estimation with Deep Likelihood Models
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A comparison of selectivity estimators for range queries on metric attributes. In SIGMOD Record
Björn Blohsfeld, Dieter Korus, and Bernhard Seeger. 1999 · 1999
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Range selectivity estimation for continuous attributes. In ssdbm
Flip Korn, Theodore Johnson, and HV Jagadish. 1999 · 1999
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Approximating multi-dimensional aggregate range queries over real attributes. In SIGMOD Record
Dimitrios Gunopulos, George Kollios, Vassilis J Tsotras, and Carlotta Domeniconi. 2000 · 2000
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One-dimensional and multi-dimensional substring selectivity estimation
HV Jagadish, Olga Kapitskaia, Raymond T Ng, and Divesh Srivastava. 2000 · 2000
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Optimal histograms for hierarchical range queries. In PODS
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Estimating the selectivity of XML path expressions for internet scale applications. In VLDB
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STHoles: a multidimensional workload-aware histogram. In SIGMOD
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Independence is good: Dependency-based histogram synopses for high-dimensional data
Amol Deshpande, Minos Garofalakis, and Rajeev Rastogi. 2001 · 2001
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Selectivity estimation using probabilistic models. In ACM SIGMOD Record , Vol. 30. ACM, 461–472
Lise Getoor, Benjamin Taskar, and Daphne Koller. 2001 · 2001
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Global optimization of histograms
HV Jagadish, Hui Jin, Beng Chin Ooi, and Kian-Lee Tan. 2001 · 2001
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Selectivity estimation of complex spatial queries. In International Symposium on Spatial and Temporal Databases . 155–174
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LEO-DB2’s learning optimizer. In VLDB
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Fast algorithms for hierarchical range histogram construction. In PODS
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SASH: A self-adaptive histogram set for dynamically changing workloads. In VLDB
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Multiscale histograms: Summarizing topological relations in large spatial datasets. In VLDB
Xuemin Lin, Qing Liu, Yidong Yuan, and Xiaofang Zhou. 2003 · 2003
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Selectivity estimation for predictive spatio-temporal queries. In ICDE
Y Tao, Jimeng Sun, and Dimitris Papadias. 2003 · 2003
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Using histograms to estimate answer sizes for XML queries
Yuqing Wu, Jignesh M Patel, and HV Jagadish. 2003 · 2003
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Multi-scale histograms for answering queries over time series data. In ICDE
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CORDS: automatic discovery of correlations and soft functional dependencies. In SIGMOD
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Qing Zhang and Xuemin Lin. 2004 · 2004
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DMT: a flexible and versatile selectivity estimation approach for graph query. In WAIM
Jianhua Feng, Qian Qian, Yuguo Liao, Guoliang Li, and Na Ta. 2005 · 2005
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Selectivity estimators for multidimensional range queries over real attributes
Dimitrios Gunopulos, George Kollios, Vassilis J Tsotras, and Carlotta Domeniconi. 2005 · 2005
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K-histograms: An efficient clustering algorithm for categorical dataset
Zengyou He, Xiaofei Xu, Shengchun Deng, and Bin Dong. 2005 · 2005
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Self-tuning, GPU-accelerated kernel density models for multidimensional selectivity estimation. In SIGMOD
Max Heimel, Martin Kiefer, and Volker Markl. 2015 · 2015
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Improving accuracy and robustness of self-tuning histograms by subspace clustering
Andranik Khachatryan, Emmanuel Müller, Christian Stier, and Klemens Böhm. 2015 · 2015
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Cardinality Estimation Using Neural Networks. In Proceedings of the 25th Annual International Conference on Computer Science and Software Engineering (CASCON ’15) . IBM Corp., Riverton, NJ, USA, 53–59
Henry Liu, Mingbin Xu, Ziting Yu, Vincent Corvinelli, and Calisto Zuzarte. 2015 · 2015
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Simultaneous discovery, estimation and prediction analysis of complex traits using a Bayesian mixture model
Gerhard Moser, Sang Hong Lee, Ben J Hayes, Michael E Goddard, Naomi R Wray, and Peter M Visscher. 2015 · 2015
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Query workload-aware overlay construction using histograms. In CIKM
Georgia Koloniari, Yannis Petrakis, Evaggelia Pitoura, and Thodoris Tsotsos. 2005 · 2005
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Dynamic histograms for non-stationary updates. In IDEAS
Elizabeth Lam and Kenneth Salem. 2005 · 2005
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Consistently estimating the selectivity of conjuncts of predicates. In PVLDB
Volker Markl, Nimrod Megiddo, Marcel Kutsch, Tam Minh Tran, P Haas, and Utkarsh Srivastava. 2005 · 2005
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AutoAdmin: Self-Tuning Database SystemsTechnology
Sanjay Agrawal, Nicolas Bruno, Surajit Chaudhuri, and Vivek R Narasayya. 2006 · 2006
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Pattern recognition and machine learning
Christopher M Bishop. 2006 · 2006
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Graph-based Synopses for Relational Selectivity Estimation. In Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data (SIGMOD ’06) . ACM, New York, NY, USA, 205–216
Joshua Spiegel and Neoklis Polyzotis. 2006 · 2006
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ISOMER: Consistent histogram construction using query feedback. In ICDE
Utkarsh Srivastava, Peter J Haas, Volker Markl, Marcel Kutsch, and Tam Minh Tran. 2006 · 2006
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Jianbo Yang, Xuejun Liao, Xin Yuan, Patrick Llull, David J Brady, Guillermo Sapiro, and Lawrence Carin. 2015 · 2015
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Structural equation models and mixture models with continuous nonnormal skewed distributions
Tihomir Asparouhov and Bengt Muthén. 2016 · 2016
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Unsupervised segmentation of cervical cell images using gaussian mixture model. In CVPR Workshops
Srikanth Ragothaman, Sridharakumar Narasimhan, Madivala G Basavaraj, and Rajan Dewar. 2016 · 2016
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Revisiting reuse for approximate query processing
Alex Galakatos, Andrew Crotty, Emanuel Zgraggen, Carsten Binnig, and Tim Kraska. 2017 · 2017
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Access Path Selection in Main-Memory Optimized Data Systems: Should I Scan or Should I Probe?. In SIGMOD
Michael S Kester, Manos Athanassoulis, and Stratos Idreos. 2017 · 2017
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Database learning: Toward a database that becomes smarter every time. In SIGMOD
Yongjoo Park, Ahmad Shahab Tajik, Michael Cafarella, and Barzan Mozafari. 2017 · 2017
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Automatic database management system tuning through large-scale machine learning. In SIGMOD
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Learned cardinalities: Estimating correlated joins with deep learning
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Query-based Workload Forecasting for Self-Driving Database Management Systems. In SIGMOD
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