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20132015
most citedGeometric Implications of the Naive Bayes Assumption

21 citations

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16 papers · 1 filter

cs.AI2014

Query DAGs: A Practical Paradigm for Implementing Belief Network Inference

Adnan Darwiche, Gregory M. Provan

We describe a new paradigm for implementing inference in belief networks, which relies on compiling a belief network into an arithmetic expression called a Query DAG (Q-DAG). Each…

cs.AI2013

Interval Influence Diagrams

Kenneth W. Fertig, John S. Breese

We describe a mechanism for performing probabilistic reasoning in influence diagrams using interval rather than point valued probabilities. We derive the procedures for node remova…

cs.AI2013

Computationally-Optimal Real-Resource Strategies

David Einav, Michael R. Fehling

This paper focuses on managing the cost of deliberation before action. In many problems, the overall quality of the solution reflects costs incurred and resources consumed in delib…

cs.AI2013

Decision Making Using Probabilistic Inference Methods

Ross D. Shachter, Mark Alan Peot

The analysis of decision making under uncertainty is closely related to the analysis of probabilistic inference. Indeed, much of the research into efficient methods for probabilist…

cs.AI2013

Integrating Model Construction and Evaluation

Robert P. Goldman, John S. Breese

To date, most probabilistic reasoning systems have relied on a fixed belief network constructed at design time. The network is used by an application program as a representation of…

cs.AI20131 cited

Reformulating Inference Problems Through Selective Conditioning

Paul Dagum, Eric J. Horvitz

We describe how we selectively reformulate portions of a belief network that pose difficulties for solution with a stochastic-simulation algorithm. With employ the selective condit…