We propose a framework which we call stochastic offline programming (SOP). The idea is to embed the development of combinatorial algorithms in an off-line learning environment whi...
Abstract We define a notion of context that represents invariant, stable-over-time behavior in an environment and we propose an algorithm for detecting context changes in a stream ...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Abstract. There are many connections between graph mining and inductive logic programming (ILP), or more generally relational learning. Up till now these connections have mostly be...
We describe the main features of SmArT, a software package providing a seamless environment for the logic and probabilistic analysis of complex systems. SmArT can combine differen...
Gianfranco Ciardo, R. L. Jones III, Andrew S. Mine...