Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
In the design of complex power distribution networks (PDN) with multiple power islands, it is required that the PDN represents a low impedance as seen by the digital modules. This...
In this paper we deal with a perturbed algebraic Riccati equation in an infinite dimensional Banach space. Besides the interest in its own right, this class of equations appears, ...
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...