Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Abstract. Monads are a well-established tool for modelling various computational effects. They form the semantic basis of Moggi’s computational metalanguage, the metalanguage of ...
In this paper, we show how pattern matching can be seen to arise from a proof term assignment for the focused sequent calculus. This use of the Curry-Howard correspondence allows ...
Hidden Markov models (HMMs) have been successfully applied to a variety of problems in molecular biology, ranging from alignment problems to gene nding and annotation. Alignment p...
We propose a type system MLFthat generalizes ML with first-class polymorphism as in System F. Expressions may contain secondorder type annotations. Every typable expression admits...