Uncertainty in Artificial Intelligence
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Proceedings of the Sixteenth Conference Conference on Uncertainty in Artificial Intelligence ( 2000 )
Jun 30- 3 2000, Stanford, CA

Edited By:
Craig Boutilier, Moises Goldszmidt
Published By: Morgan Kaufmann, San Francisco, CA
ISBN: 1-55860-709-9

A Bayesian Method for Causal Modeling and Discovery Under Selection
Gregory Cooper
A Branch-and-Bound Algorithm for MDL Learning Bayesian Networks
Jin Tian
A Complete Calculus for Possibilistic Logic Programming with Fuzzy Propositional Variables
Teresa Alsinet , Lluis Godo
A Decision Theoretic Approach to Targeted Advertising
David Chickering , David Heckerman
A Differential Approach to Inference in Bayesian Networks
Adnan Darwiche
A Knowledge Acquisition Tool for Bayesian-Network Troubleshooters
Claus Skaanning
A Principled Analysis of Merging Operations in Possibilistic Logic
Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade
A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs
Phan Giang , Prakash Shenoy
A Two-round Variant of EM for Gaussian Mixtures
Sanjoy Dasgupta , Leonard Schulman
Adaptive Importance Sampling for Estimation in Structured Domains
Luis Ortiz , Leslie Kaelbling
An Uncertainty Framework for Classification
Loo-Nin Teow , Kia-Fock Loe
Any-Space Probabilistic Inference
Adnan Darwiche
Approximately Optimal Monitoring of Plan Preconditions
Craig Boutilier
Bayesian Classification and Feature Selection from Finite Data Sets
Frans Coetzee , Steve Lawrence , C. Giles
Being Bayesian about Network Structure
Nir Friedman , Daphne Koller
Building a Stochastic Dynamic Model of Application Use
Peter Gorniak , David Poole
Causal Mechanism-based Model Construction
Tsai-Ching Lu , Marek Druzdzel , Tze-Yun Leong
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory- and Model-Based Approach
David Pennock , Eric Horvitz , Steve Lawrence , C. Giles
Combinatorial Optimization by Learning and Simulation of Bayesian Networks
Pedro Larrañaga , Ramon Etxeberria , Jose Lozano , Jose Pena
Combining Feature and Prototype Pruning by Uncertainty Minimization
Marc Sebban , Richard Nock
Compact Securities Markets for Pareto Optimal Reallocation of Risk
David Pennock , Michael Wellman
Computational Investigation of Low-Discrepancy Sequences in Simulation Algorithms for Bayesian Networks
Jian Cheng , Marek Druzdzel
Conditional Independence and Markov Properties in Possibility Theory
Jirina Vejnarova
Conditional Plausibility Measures and Bayesian Networks
Joseph Halpern
Conversation as Action Under Uncertainty
Tim Paek , Eric Horvitz
Credal Networks under Maximum Entropy
Thomas Lukasiewicz
Dependency Networks for Collaborative Filtering and Data Visualization
David Heckerman , David Chickering , Christopher Meek , Robert Rounthwaite , Carl Kadie
Dynamic Bayesian Multinets
Jeff Bilmes
Dynamic Trees: A Structured Variational Method Giving Efficient Propagation Rules
Amos Storkey
Evaluating Influence Diagrams using LIMIDs
Dennis Nilsson , Steffen Lauritzen
Experiments with Random Projection
Sanjoy Dasgupta
Exploiting Qualitative Knowledge in the Learning of Conditional Probabilities of Bayesian Networks
Frank Wittig , Anthony Jameson
Fast Planning in Stochastic Games
Michael Kearns , Yishay Mansour , Satinder Singh
Feature Selection and Dualities in Maximum Entropy Discrimination
Tony Jebara , Tommi Jaakkola
Game Networks
Pierfrancesco La Mura
Gaussian Process Networks
Nir Friedman , Iftach Nachman
Inference for Belief Networks Using Coupling From the Past
Michael Harvey , Radford Neal
Learning Graphical Models of Images, Videos and Their Spatial Transformations
Brendan Frey , Nebojsa Jojic
Learning to Cooperate via Policy Search
Leonid Peshkin , Kee-Eung Kim , Nicolas Meuleau , Leslie Kaelbling
Likelihood Computations Using Value Abstractions
Nir Friedman , Dan Geiger , Noam Lotner
Making Sensitivity Analysis Computationally Efficient
Uffe Kjærulff , Linda van der Gaag
Marginalization in Composed Probabilistic Models
Radim Jirousek
Maximum Entropy and the Glasses You Are Looking Through
Peter Grunwald
Minimum Message Length Clustering Using Gibbs Sampling
Ian Davidson
Mix-nets: Factored Mixtures of Gaussians in Bayesian Networks With Mixed Continuous And Discrete Variables
Scott Davies , Andrew Moore
Model Criticism of Bayesian Networks with Latent Variables
David Williamson , Russell Almond , Robert Mislevy
Model-Based Hierarchical Clustering
Shivakumar Vaithyanathan , Byron Dom
Monte Carlo Inference via Greedy Importance Sampling
Dale Schuurmans , Finnegan Southey
Nash Convergence of Gradient Dynamics in Iterated General-Sum Games
Satinder Singh , Michael Kearns , Yishay Mansour
On the Use of Skeletons when Learning in Bayesian Networks
Harald Steck
PEGASUS: A Policy Search Method for Large MDPs and POMDPs
Andrew Ng , Michael Jordan
Perfect Tree-Like Markovian Distributions
Ann Becker , Dan Geiger , Christopher Meek
Pivotal Pruning of Trade-offs in QPNs
Silja Renooij , Linda van der Gaag , Simon Parsons , Shaw Green
Policy Iteration for Factored MDPs
Daphne Koller , Ron Parr
Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning
Michael Horsch , Bill Havens
Probabilistic Models for Agents' Beliefs and Decisions
Brian Milch , Daphne Koller
Probabilistic Models for Query Approximation with Large Sparse Binary Datasets
Dmitry Pavlov , Heikki Mannila , Padhraic Smyth
Probabilistic State-Dependent Grammars for Plan Recognition
David Pynadath , Michael Wellman
Probabilities of Causation: Bounds and Identification
Jin Tian , Judea Pearl
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Arnaud Doucet , Nando de Freitas , Kevin Murphy , Stuart Russell
Representing and Solving Asymmetric Bayesian Decision Problems
Thomas Nielsen , Finn Jensen
Reversible Jump MCMC Simulated Annealing for Neural Networks
Christophe Andrieu , Nando de Freitas , Arnaud Doucet
Risk Agoras: Dialectical Argumentation for Scientific Reasoning
Peter McBurney , Simon Parsons
Separation Properties of Sets of Probability Measures
Fabio Cozman
Stochastic Logic Programs: Sampling, Inference and Applications
James Cussens
The Anchors Hierachy: Using the triangle inequality to survive high dimensional data
Andrew Moore
The Complexity of Decentralized Control of Markov Decision Processes
Daniel Bernstein , Shlomo Zilberstein , Neil Immerman
Tractable Bayesian Learning of Tree Belief Networks
Marina Meila , Tommi Jaakkola
User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks
Haiqin Wang , Marek Druzdzel
Using ROBDDs for Inference in Bayesian Networks with Troubleshooting as an Example
Thomas Nielsen , Pierre-Henri Wuillemin , Finn Jensen , Uffe Kjærulff
Utilities as Random Variables: Density Estimation and Structure Discovery
Urszula Chajewska , Daphne Koller
Value-Directed Belief State Approximation for POMDPs
Pascal Poupart , Craig Boutilier
Variational Approximations between Mean Field Theory and the Junction Tree Algorithm
Wim Wiegerinck
Variational Relevance Vector Machines
Christopher Bishop , Michael Tipping
YGGDRASIL - A Statistical Package for Learning Split Models
Soren Hojsgaard

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