Skip to contents

select private candidate constructor

Source: R/combinators.R
make_select_private_candidate.Rd

Select a private candidate whose score is above a threshold.

Usage

make_select_private_candidate(measurement, stop_probability, threshold)

Arguments

measurement

A measurement that releases a 2-tuple of (score, candidate)

stop_probability

The probability of stopping early at any iteration.

threshold

The threshold score. Return immediately if the score is above this threshold.

Value

A measurement that returns a release from measurement whose score is greater than threshold, or none.

Details

Given measurement that satisfies ε-DP, returns new measurement M' that satisfies 2ε-DP. M' releases the first invocation of measurement whose score is above threshold.

Each time a score is below threshold the algorithm may terminate with probability stop_probability and return nothing.

measurement should make releases in the form of (score, candidate). If you are writing a custom scorer measurement in Python, specify the output type as TO=(float, "ExtrinsicObject"). This ensures that the float value is accessible to the algorithm. The candidate, left as arbitrary Python data, is held behind the ExtrinsicObject.

Algorithm 1 in Private selection from private candidates <https://arxiv.org/pdf/1811.07971.pdf#page=7>_ (Liu and Talwar, STOC 2019).

Required features: contrib

make_select_private_candidate in Rust documentation.

Supporting Elements:

  • Input Domain: DI

  • Output Type: Option<(f64, TO)>

  • Input Metric: MI

  • Output Measure: MaxDivergence

Proof Definition:

(Proof Document)