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Quality and Efficiency in Kernel Density Estimates for Large Data
Summary: Randomized and deterministic KDE algorithms with quality guarantees for huge data; no kernel or bandwidth knowledge required. Highly parallelizable, MapReduce-friendly; orders-of-magnitude efficiency gains with strong empirical validation on real data.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 4726
- Venue
- SIGMOD
- Year
- 2013
- Pagerank
- 7.2381634e-05
- Overall Rank
- 3,313 | 76.96%
- DOI
-
-
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 3,968 |
QUAD: Quadratic-Bound-based Kernel Density Visualization |
2020 |
SIGMOD |
6.5793715e-05 |
| 4,584 |
Scalable Kernel Density Classification via Threshold-Based Pruning |
2017 |
SIGMOD |
6.0668364e-05 |
| 5,909 |
At-the-time and Back-in-time Persistent Sketches |
2021 |
SIGMOD |
5.2769377e-05 |
| 9,495 |
Fast Network K-function-based Spatial Analysis |
2022 |
VLDB |
4.3341665e-05 |
| 11,002 |
LION: Fast and High-Resolution Network Kernel Density Visualization |
2024 |
VLDB |
4.1945683e-05 |
| 11,128 |
LARGE: A Length-Aggregation-based Grid Structure for Line Density Visualization |
2024 |
VLDB |
4.1945683e-05 |
| 11,334 |
SLAM: Efficient Sweep Line Algorithms for Kernel Density Visualization |
2022 |
SIGMOD |
4.1945683e-05 |
| 11,417 |
SAFE: A Share-and-Aggregate Bandwidth Exploration Framework for Kernel Density Visualization |
2022 |
VLDB |
4.1945683e-05 |
| 11,421 |
SWS: A Complexity-Optimized Solution for Spatial-Temporal Kernel Density Visualization |
2022 |
VLDB |
4.1945683e-05 |
| 11,499 |
Fast Augmentation Algorithms for Network Kernel Density Visualization |
2021 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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