A randomized mechanism is calibrated so similar datasets with or without one record produce close output distributions. Privacy accounting tracks the cumulative guarantee as multiple analyses or training steps consume a budget.
Differential privacy is a mathematical framework for limiting how much an output can reveal about any one person's data.
A randomized mechanism is calibrated so similar datasets with or without one record produce close output distributions. Privacy accounting tracks the cumulative guarantee as multiple analyses or training steps consume a budget.