The type-theoretic explanation of modules proposed to date (for programming languages like ML) is unsatisfactory, because it does not capture that evaluation of type-expressions i...
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
This paper is an exploration in a functional programming framework of isomorphisms between elementary data types (natural numbers, sets, finite functions, permutations binary deci...
Detecting whether a finite execution trace (or a computation) of a distributed program satisfies a given predicate, called predicate detection, is a fundamental problem in distr...
d Abstract) Naoshi Tabuchi Eijiro Sumii Akinori Yonezawa 1 Department of Computer Science, Graduate School of Information Science and Technology, University of Tokyo We present re...