Variational EM has become a popular technique in probabilistic NLP with hidden variables. Commonly, for computational tractability, we make strong independence assumptions, such a...
In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in ter...
Will Bridewell, Pat Langley, Ljupco Todorovski, Sa...
This paper proposes a definition of magnetic vector potential that can be used to evaluate sparse partial inductance matrices. Unlike the commonly applied procedure of discarding...
This work is motivated by the necessity to automate the discovery of structure in vast and evergrowing collection of relational data commonly represented as graphs, for example ge...
The Cyc KB has a rich pre-existing ontology for representing common sense knowledge. To clarify and enforce its terms’ semantics and to improve inferential efficiency, the Cyc on...
John Cabral, Robert C. Kahlert, Cynthia Matuszek, ...