Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
If we limit the contact rate of worm traffic, can we alleviate and ultimately contain Internet worms? This paper sets out to answer this question. Specifically, we are interested ...
Cynthia Wong, Chenxi Wang, Dawn Xiaodong Song, Sta...
We study the dynamics of a simple bistable system driven by multiplicative correlated noise. Such system mimics the dynamics of classical attractor neural networks with an addition...
Traffic Congestion is a multi-billion dollar national problem and worsening every year with population growth and increase in freight traffic. We present a model for realistic s...