There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative ...
We dene the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of goal propositions, a probability threshold, ...
This paper develops connections between objective Bayesian epistemology--which holds that the strengths of an agent's beliefs should be representable by probabilities, should...
We introduce the posterior probabilistic clustering (PPC), which provides a rigorous posterior probability interpretation for Nonnegative Matrix Factorization (NMF) and removes th...
Hash-consing is a technique to share values that are structurally equal. Beyond the obvious advantage of saving memory blocks, hash-consing may also be used to speed up fundamenta...