Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
This paper presents an efficient statistical design methodology that allows simultaneous sizing for performance and optimization for yield and robustness of analog circuits. The s...
Abstract— While packet capture has been observed in real implementations of 802.11 devices, there is a lack of accurate models that describe the phenomenon. We present a general ...
Objective: Deep biomedical models are often expressed by means of differential equations. Despite their expressive power, they are difficult to reason about and make decisions, g...
—The objective of this paper is to study how algorithms of optimization affect the parametersestimation of Autoregressive AR(1)Models. In our research we have represented the AR...