This paper describes an optimization framework for reconstructing nonnegative image intensities from linear projections contaminated with Poisson noise. Such Poisson inverse probl...
Rebecca Willett, Zachary T. Harmany, Roummel F. Ma...
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
— In this paper, we describe a novel localization method for ad hoc wireless sensor networks. Accurate selforganization and localization is an essential characteristic of high pe...
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
This paper investigates reinforcement learning (RL) in XCS. First, it formally shows that XCS implements a method of generalized RL based on linear approximators, in which the usu...