BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics
Summary: BlazeIt (FRAMEQL) provides a declarative SQL-like layer for video analytics over neural annotations, enabling optimized spatiotemporal queries. NN control variates for fast, error-bounded aggregations and a cardinality-limited query search yield up to 83x speedups over prior work. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Daniel Kang
- 2. Peter Bailis
- 3. Matei Zaharia
Incoming Citations (Sorted by Pagerank)
Showing 2 of 52 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,426 | Accelerating Queries over Unstructured Data with ML | 2021 | CIDR | 4.1945683e-05 |
| 11,482 | Pool of Experts: Realtime Querying Specialized Knowledge in Massive Neural Networks | 2021 | SIGMOD | 4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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