To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
The evaluation of new network server architectures is usually performed experimentally using either a simulator or a hardware prototype. Accurate simulation of the hardwaresoftwar...
Abstract. We relate two well-studied methodologies in deductive verification of operationally modeled sequential programs, namely the use of inductive invariants and clock functio...
— A formal methodology for the analysis of a closed loop clock distribution and active deskewing network is proposed. In this paper an active clock distribution and deskewing net...
In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...