We describe a framework called the Uni-Level Description (ULD) for accurately representing information from a broad range of data models. The ULD extends previous metadata-model a...
This paper defines a type of constrained artificial neural network (ANN) that enables analytical certification arguments whilst retaining valuable performance characteristics. ...
This paper describes a safe and efficient combination of the object-based message-driven execution and shared array parallel programming models. In particular, we demonstrate how ...
Phil Miller, Aaron Becker, Laxmikant V. Kalé...
This paper describes a type system that is capable of expressing and enforcing immutability constraints. The speonstraint expressed is that the abstract state of the object to whi...
We present a new series of distributed constraint satisfaction algorithms, the distributed breakout algorithms, which is inspired by local search algorithms for solving the constr...