This paper presents a novel method for multi-relational classification via an aggregation-based Inductive Logic Programming (ILP) approach. We extend the classical ILP representati...
Abstract. We propose a flexible method for verifying the security of ML programs that use cryptography and recursive data structures. Our main applications are X.509 certificate ch...
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
Abstract This work studies the properties of finite automata recognizing vectors with real components, encoded positionally in a given integer numeration base. Such automata are us...
This work develops an integrated approach to the verification of behaviourally rich programs, founded directly on operational semantics. The power of the approach is demonstrated ...