We formalize a model for supervised learning of action strategies in dynamic stochastic domains and show that PAC-learning results on Occam algorithms hold in this model as well. W...
In discrete event systems, a given task can start executing when all the required input data are available. The required input data for a given task may change along the evolution...
``Church's thesis'' is at the foundation of computer science. We point out that with any particular set of physical laws, Church's thesis need not merely be po...
This paper takes a computational learning theory approach to a problem of linear systems identification. It is assumed that inputs are generated randomly from a known class consist...
This paper considers the max-min quantum error recovery problem; the recovery channel to be designed maximizes the fidelity between input and output states of a given noisy channel...