A bisimulation-invariant synthesis framework for optimal predicate pushdown in fold-based UDFs produces correct transformations that speed up 150 real pipelines by 2.4x on average.
Venkatesh Emani, Karthik Ramachandra, Subhro Bhattacharya, and S
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Tab-PE extends Private Evolution to tabular data with heuristic operators, outperforming AIM by up to 10% classification accuracy and 28x speed on high-order correlation datasets under differential privacy.
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Optimal Predicate Pushdown Synthesis
A bisimulation-invariant synthesis framework for optimal predicate pushdown in fold-based UDFs produces correct transformations that speed up 150 real pipelines by 2.4x on average.
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Differentially Private Synthetic Data via APIs 4: Tabular Data
Tab-PE extends Private Evolution to tabular data with heuristic operators, outperforming AIM by up to 10% classification accuracy and 28x speed on high-order correlation datasets under differential privacy.