In recent times, the functioning of various aspects of modern society—ranging from the
various infrastructural utilities such as electrical power, water to socio-economical aspects …

Differential privacy is a notion of confidentiality that allows useful computations on sensible
data while protecting the privacy of individuals. Proving differential privacy is a difficult and …

Currently published HOL formalizations of measure theory concentrate on the Lebesgue
integral and they are restricted to real-valued measures. We lift this restriction by introducing …

The Bayesian approach to machine learning amounts to inferring posterior distributions of
random variables from a probabilistic model of how the variables are related (that is, a prior …

In the recent years, numerous proof systems have improved enough to be used for formally
verifying non-trivial mathematical results. They, however, have different purposes and it is …

We report on an original formalization of measure and integration theory in the Coq proof
assistant. We build the Lebesgue measure following a standard construction that had not yet …

Abstract Reliability Block Diagrams (RBDs) allow us to model the failure relationships of
complex systems and their sub-components and are extensively used for system reliability …

The Bayesian approach to machine learning amounts to computing posterior distributions of
random variables from a probabilistic model of how the variables are related (that is, a prior …

Reliability Block Diagrams (RBDs) allow us to model the failure relationships of complex
systems and their sub-components and are extensively used for system reliability …

Dependability is an umbrella concept that subsumes many key properties about a system,
including reliability, maintainability, safety, availability, confidentiality, and integrity. Various …