Efficient and Effective Cardinality Estimation for Skyline Family
Summary: EECE unifies skyline variants into a single end-to-end estimator; learning distributions and enforcing monotonicity. Incremental learning with a mixture-data guided transformer and monotonicity clamping yields six-order speedup and 39% accuracy gain over SOTA. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Xiaoye Miao
- 2. Yangyang Wu
- 3. Jiazhen Peng
- 4. Yunjun Gao
- 5. Jianwei Yin
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