We take another look at the general problem of selecting a preferred probability measure among those that comply with some given constraints. The dominant role that entropy maximi...
Qualitativeprobabilistic reasoningin a Bayesiannetworkoften reveals tradeoffs: relationships that are ambiguousdue to competingqualitative influences. Wepresent twotechniquesthat ...
We describe computationally efficient methods for learning mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs). We argue that simple...
Bo Thiesson, Christopher Meek, David Maxwell Chick...
Causal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three successively more general classes of...
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...