We present a technique that improves the efficiency of word-lattice parsing as used in speech recognition language modeling. Our technique applies a probabilistic parser iterative...
We examine the marriage of recent probabilistic generative models for social networks with classical frameworks from mathematical economics. We are particularly interested in how ...
Sham M. Kakade, Michael J. Kearns, Luis E. Ortiz, ...
We consider the question of how well a given distribution can be approximated with probabilistic graphical models. We introduce a new parameter, effective treewidth, that captures...
The Dempster-Shafer (DS) theory of probabilistic reasoning is presented in terms of a semantics whereby every meaningful formal assertion is associated with a triple (p, q, r) whe...
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to nondifferentiable objective functions and trades off explor...