By using a macro/micro state model we show how assumptions on the resolution of logical and physical timing of computation in computer systems has resulted in design methodologies...
We study algorithmic problems in multi-stage open shop processing systems that are centered around reachability and deadlock detection questions. We characterize safe and unsafe s...
Christian Eggermont, Alexander Schrijver, Gerhard ...
We describe a method for the fully automatic learning of hierarchical finite state translation models. The input to the method is transcribed speech utterances and their correspon...
Abstract - We address the problem of automatically verifying large digital designs at the logic level, against high-level specifications. In this paper, we present a methodology wh...
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...