We describe a new approach for understanding the difficulty of designing efficient learning algorithms. We prove that the existence of an efficient learning algorithm for a circui...
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
Tree Augmented Naive Bayes (TAN) has shown to be competitive with state-of-the-art machine learning algorithms [3]. However, the TAN induction algorithm that appears in [3] can be...
Abstract. This paper presents an exemplar-based approach to detecting and localizing human actions, such as running, cycling, and swinging, in realistic videos with dynamic backgro...
Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...