Sciweavers

UAI
1998
13 years 5 months ago
An Anytime Algorithm for Decision Making under Uncertainty
We present an anytime algorithm which computes policies for decision problems represented as multi-stage influence diagrams. Our algorithm constructs policies incrementally, start...
Michael C. Horsch, David Poole
UAI
1998
13 years 5 months ago
Large Deviation Methods for Approximate Probabilistic Inference
We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
Michael J. Kearns, Lawrence K. Saul
UAI
1998
13 years 5 months ago
Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
People using consumer software applications typically do not use technical jargon when querying an online database of help topics. Rather, they attempt to communicate their goals ...
David Heckerman, Eric Horvitz
UAI
1998
13 years 5 months ago
Axiomatizing Causal Reasoning
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...
Joseph Y. Halpern
UAI
1998
13 years 5 months ago
Hierarchical Solution of Markov Decision Processes using Macro-actions
tigate the use of temporally abstract actions, or macro-actions, in the solution of Markov decision processes. Unlike current models that combine both primitive actions and macro-...
Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kae...
UAI
1998
13 years 5 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
UAI
1998
13 years 5 months ago
The Bayesian Structural EM Algorithm
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
Nir Friedman
UAI
1998
13 years 5 months ago
Utility Elicitation as a Classification Problem
The majority of real-world probabilistic systems are used by more than one user, thus a utility model must be elicited separately for each newuser. Utility elicitation is long and...
Urszula Chajewska, Lise Getoor, Joseph Norman, Yuv...
UAI
1998
13 years 5 months ago
Empirical Analysis of Predictive Algorithms for Collaborative Filtering
John S. Breese, David Heckerman, Carl Myers Kadie