UAI
1998
13 years 5 months ago
1998
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...
UAI
1998
13 years 5 months ago
1998
UAI
1998
13 years 5 months ago
1998
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...
UAI
1998
13 years 5 months ago
1998
The process of diagnosis involves learning about the state of a system from various observations of symptoms or findings about the system. Sophisticated Bayesian (and other) algor...
UAI
1998
13 years 5 months ago
1998
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these app...
UAI
1998
13 years 5 months ago
1998
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
UAI
1998
13 years 5 months ago
1998
We examine methods for clustering in high dimensions. In the first part of the paper, we perform an experimental comparison between three batch clustering algorithms: the Expectat...
UAI
1998
13 years 5 months ago
1998
Qualitativeprobabilistic reasoningin a Bayesiannetworkoften reveals tradeoffs: relationships that are ambiguousdue to competingqualitative influences. Wepresent twotechniquesthat ...
UAI
1998
13 years 5 months ago
1998
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...
UAI
1998
13 years 5 months ago
1998
