What ε Actually Buys: Checking a Privacy Guarantee Against Its Own Definition, Not a Simulation
This story is from 2026-08-31. It is preserved in the archive; the latest stories are on the live feed.
Three days of this series asked what a promise about a model is worth: what a clustering score is a number of, which fairness equalities can hold at once, what the bound printed in front of a training run guarantees. This is the promise attached to the data — that a release is safe to publish. Run…
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- 2026-08-31 02:08 · DEV Community — Machine Learning
What ε Actually Buys: Checking a Privacy Guarantee Against Its Own Definition, Not a Simulation
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