Sciweavers

UAI
1998
14 years 1 months ago
Incremental Tradeoff Resolution in Qualitative Probabilistic Networks
Qualitativeprobabilistic reasoningin a Bayesiannetworkoften reveals tradeoffs: relationships that are ambiguousdue to competingqualitative influences. Wepresent twotechniquesthat ...
Chao-Lin Liu, Michael P. Wellman
UAI
1998
14 years 1 months ago
Measure Selection: Notions of Rationality and Representation Independence
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...
Manfred Jaeger
UAI
1998
14 years 1 months ago
Any Time Probabilistic Reasoning for Sensor Validation
Pablo H. Ibargüengoytia, Luis Enrique Sucar, ...
UAI
1998
14 years 1 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
14 years 1 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
14 years 1 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
14 years 1 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
14 years 1 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
14 years 1 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