LAPRAS uses predictions to answer likely queries with the offline Matrix Mechanism and paces residual budget for unpredicted queries via unbiased stopping-time estimation from the first few unexpected arrivals, achieving near-offline utility when overlap is high.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
A new abstract interpretation algorithm enables sound optimistic analysis of e-graphs during equality saturation, unifying it with non-destructive rewriting and improving precision on cyclic SSA programs.
citing papers explorer
-
LAPRAS : Learning-Augmented PRivate Answering for linear query Streams
LAPRAS uses predictions to answer likely queries with the offline Matrix Mechanism and paces residual budget for unpredicted queries via unbiased stopping-time estimation from the first few unexpected arrivals, achieving near-offline utility when overlap is high.
-
Optimism in Equality Saturation
A new abstract interpretation algorithm enables sound optimistic analysis of e-graphs during equality saturation, unifying it with non-destructive rewriting and improving precision on cyclic SSA programs.