The paradigm of advisable planning, in which a user provides guidance to influence the content of solutions produced by an underlying planning system, holds much promise for impro...
Planning by forward chaining through the world space has long been dismissed as being "obviously" infeasible. Nevertheless, this approach to planning has many advantages...
The paper studies empirically the time-space trade-off between sampling and inference in the cutset sampling algorithm. The algorithm samples over a subset of nodes in a Bayesian ...
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...