The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
We briefly survey several privacy compromises in published datasets, some historical and some on paper. An inspection of these suggests that the problem lies with the nature of the...
We present an approach on how to investigate what kind of semantic information is regularly associated with the structural markup of scientific articles. This approach addresses ...
Abstract Constraint logic programming (CLP) is a generalization of the pure logic programming paradigm, having similar model-theoretic, fixpoint and operational semantics [9]. Sinc...
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...