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Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation

Summary: Self-tuning, GPU-accelerated KDE for multidimensional selectivity estimation; numeric optimization and continuous adaptation to data and workload. Experiments show scalable models that adapt to changes and outperform both KDE baselines and state-of-the-art multidimensional histograms. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5056
Venue
SIGMOD
Year
2015
Pagerank
9.3879598e-05
Overall Rank
2,167 | 84.95%
DOI
10.1145/2723372.2749438

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 32 of 32 citing papers.

Rank Citing Paper Year Venue Pagerank
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
1,239 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00013091459
1,638 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00011050093
1,699 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010848882
1,727 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00010731889
2,153 The Data Calculator*: Data Structure Design and Cost Synthesis from First Principles and Learned Cost Models 2018 SIGMOD 9.418541e-05
2,769 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 8.1512848e-05
2,971 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 7.7935535e-05
3,455 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 7.0760196e-05
3,471 GPL: A GPU-based Pipelined Query Processing Engine 2016 SIGMOD 7.0628019e-05
3,492 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 7.0435484e-05
3,924 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 6.6227223e-05
3,955 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 6.5895015e-05
3,992 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 6.5519369e-05
4,273 Similarity Query Processing for High-Dimensional Data 2020 VLDB 6.2932217e-05
4,543 FACE: A Normalizing Flow based Cardinality Estimator 2022 VLDB 6.0953507e-05
4,815 DigitHist: a Histogram-Based Data Summary with Tight Error Bounds 2017 VLDB 5.8978716e-05
5,313 Key-Value Storage Engines 2020 SIGMOD 5.5711707e-05
5,630 Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach 2020 SIGMOD 5.4010111e-05
5,886 COMPASS: Online Sketch-based Query Optimization for In-Memory Databases 2021 SIGMOD 5.2847297e-05
6,365 Pre-training Summarization Models of Structured Datasets for Cardinality Estimation 2022 VLDB 5.0892829e-05
6,367 Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs 2021 VLDB 5.0887599e-05
6,440 From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems 2019 SIGMOD 5.0546781e-05
7,155 Evaluating Multi-GPU Sorting with Modern Interconnects 2022 SIGMOD 4.810361e-05
8,095 Grep: A Graph Learning Based Database Partitioning System 2023 SIGMOD 4.5837691e-05
8,383 Consistent and Flexible Selectivity Estimation for High-Dimensional Data 2021 SIGMOD 4.5261239e-05
9,387 Small Selectivities Matter: Lifting the Burden of Empty Samples 2021 SIGMOD 4.341968e-05
9,662 Efficient Query Re-optimization with Judicious Subquery Selections 2023 SIGMOD 4.3056334e-05
9,690 Selectivity Estimation for Queries Containing Predicates over Set-Valued Attributes 2023 SIGMOD 4.2994116e-05
9,877 PRICE: A Pretrained Model for Cross-Database Cardinality Estimation 2025 VLDB 4.2615675e-05
11,087 Presto’s History-based Query Optimizer 2024 VLDB 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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