Dynamically reconfigurable embedded systems offer potential for higher performance as well as adaptability to changing system requirements at low cost. Such systems employ run-tim...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
Efficient and robust metacomputing requires the decomposition of complex jobs into tasks that must be scheduled on distributed processing nodes. There are various ways of creating...
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...
Software architecture is important for large systems in which it is the main means for, among other things, controlling complexity. Current ideas on software architectures were no...