Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
In this paper we propose a new framework for designing a delay differential equation (DDE) solver which works with any supplied initial value problem (IVP) solver that is based on...
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy, usually the most precious resource in battery-powered ...
Adam Silberstein, Carla Schlatter Ellis, Jun Yang ...
A simple analytical model is proposed here that captures to a large extent the kinematic structure of rat exploratory behavior. Previous studies have shown that such behavior consi...
In this paper, we present a new hybrid branch predictor called the GoStay2, which can effectively reduce indirect misprediction rates. The GoStay2 has two different mechanisms comp...