English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The extensive deployment of probabilistic algorithms has radically changedour perspective on several well-established computational notions. Correctnessis probably the most basic one. While a typical probabilistic program cannot besaid to compute the correct result, we often have quite strong expectationsabout the frequency with which it should return certain outputs. In thesecases, trust as a generalisation of correctness fares better. One way tounderstand it is to say that a probabilistic computational process istrustworthy if the frequency of its outputs is compliant with a probabilitydistribution which models its expected behaviour. We present a formalcomputational framework that formalises this idea. In order to do so, we definea typed lambda-calculus that features operators for conducting experiments atruntime on probabilistic programs and for evaluating whether they computeoutputs as determined by a target probability distribution. After proving somefundamental computational properties of the calculus, such as progress andtermination, we define a static notion of confidence that allows to prove thatour notion of trust behaves correctly with respect to the basic tenets ofprobability theory.

A Typed Lambda-Calculus for Establishing Trust in Probabilistic Programs