MAST: Towards Efficient Analytical Query Processing on Point Cloud Data
Summary: MAST enables approximate analytics on point clouds by sampling core frames under a budget to minimize DL calls. It fuses multi-agent RL sampling with a spatio-temporal index to accelerate PC retrieval and aggregates, with provable error bounds. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jiangneng Li
- 2. Haitao Yuan
- 3. Gao Cong
- 4. Han Mao Kiah
- 5. Shuhao Zhang
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,447 | Demonstrating MAST: An Efficient System for Point Cloud Data Analytics | 2025 | SIGMOD | 4.1905499e-05 |
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