Uncertainty in Artificial Intelligence
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Proceedings of the Eighteenth Conference Conference on Uncertainty in Artificial Intelligence ( 2002 )
Aug 1-4 2002, Alberta,Canada

Edited By:
Adnan Darwiche, Nir Friedman
Published By: Morgan Kaufmann, San Francisco, CA
ISBN: 1-55860-897-4

A Bayesian Network Scoring Metric That Is Based On Globally Uniform Parameter Priors
Mehmet Kayaalp , Gregory Cooper
A constraint satisfaction approach to the robust spanning tree problem with interval data
Ionut Aron , Pascal Van Hentenryck
A New Class of Upper Bounds on the Log Partition Function
Martin Wainwright , Tommi Jaakkola , Alan Willsky
Adaptive Foreground and Shadow Detection inImage Sequences
Yang Wang , Tele Tan
Advances in Boosting (Invited Talk)
Robert Schapire
Almost-everywhere algorithmic stability and generalization error
Samuel Kutin , Partha Niyogi
An Information-Theoretic External Cluster-Validity Measure
Byron Dom
An MDP-based Recommender System
Guy Shani , Ronen Brafman , David Heckerman
Anytime State-Based Solution Methods for Decision Processes with non-Markovian Rewards
Sylvie Thiebaux , Froduald Kabanza , John Slanley
Asymptotic Model Selection for Naive Bayesian Networks
Dmitry Rusakov , Dan Geiger
Bayesian Network Classifiers in a High Dimensional Framework
Tatjana Pavlenko , Dietrich von Rosen
Bipolar Possibilistic Representations
Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade
Causes and Explanations in the Structural-Model Approach: Tractable Cases
Thomas Eiter , Thomas Lukasiewicz
CFW: A Collaborative Filtering System Using Posteriors Over Weights Of Evidence
Carl Kadie , Christopher Meek , David Heckerman
Complexity of Mechanism Design
Vincent Conitzer , Tuomas Sandholm
Continuation Methods for Mixing Heterogenous Sources
Adrian Corduneanu , Tommi Jaakkola
Continuous Time Bayesian Networks
Uri Nodelman , Christian Shelton , Daphne Koller
Coordinates: Probabilistic Forecasting of Presence and Availability
Eric Horvitz , Paul Koch , Carl Kadie , Andy Jacobs
Decayed MCMC Filtering
Bhaskara Marthi , Hanna Pasula , Stuart Russell , Yuval Peres
Decision Principles to justify Carnap's Updating Method and to Suggest Corrections of Probability Judgments (Invited Talks)
Peter Wakker
Dimension Correction for Hierarchical Latent Class Models
Tomas Kocka , Nevin Zhang
Discriminative Probabilistic Models for Relational Data
Ben Taskar , Pieter Abbeel , Daphne Koller
Distributed Planning in Hierarchical Factored MDPs
Carlos Guestrin , Geoffrey Gordon
Efficient Nash Computation in Large Population Games with Bounded Influence
Michael Kearns , Yishay Mansour
Expectation Propogation for approximate inference in dynamic Bayesian networks
Tom Heskes , Onno Zoeter
Expectation-Propogation for the Generative Aspect Model
Thomas Minka , John Lafferty
Exploiting Functional Dependence in Bayesian Network Inference
Jirka Vomlel
Factored Particles for Scalable Monitoring
Brenda Ng , Leonid Peshkin , Avi Pfeffer
Factorization of Discrete Probability Distributions
Dan Geiger , Christopher Meek , Bernd Sturmfels
Finding Optimal Bayesian Networks
David Chickering , Christopher Meek
Formalizing Scenario Analysis
Peter McBurney , Simon Parsons
From Qualitative to Quantitative Probabilistic Networks
Silja Renooij , Linda van der Gaag
General Lower Bounds based on Computer Generated Higher Order Expansions
Martijn Leisink , Hilbert Kappen
Generalized Instrumental Variables
Carlos Brito , Judea Pearl
Inductive Policy Selection for First-Order MDPs
Sung Wook Yoon , Alan Fern , Robert Givan
Inference with Seperately Specified Sets of Probabilities in Credal Networks
Jose Ferreira da Rocha , Fabio Cozman
Interpolating Conditional Density Trees
Scott Davies , Andrew Moore
Introducing Variable Importance Tradeoffs into CP-Nets
Ronen Brafman , Carmel Domshlak
IPF for Discrete Chain Factor Graphs
Wim Wiegerinck , Tom Heskes
Iterative Join-Graph Propagation
Rina Dechter , Kalev Kask , Robert Mateescu
Learning Hierarchical Object Maps Of Non-Stationary Environments with mobile robots
Dragomir Anguelov , Rahul Biswas , Daphne Koller , Benson Limketkai , Sebastian Thrun
Learning with Scope, with Application to Information Extraction and Classification
David Blei , J Bagnell , Andrew McCallum
Loopy Belief Propogation and Gibbs Measures
Sekhar Tatikonda , Michael Jordan
MAP Complexity Results and Approximation Methods
James Park
Markov Equivalence Classes for Maximal Ancestral Graphs
Ayesha Ali , Thomas Richardson
Mechanism Design with Execution Uncertainty
Ryan Porter , Amir Ronen , Yoav Shoham , Moshe Tennenholtz
Modelling Information Incorporation in Markets, with Application to Detecting and Explaining Events
David Pennock , Sandip Debnath , Eric Glover , C. Giles
Monitoring a Complez Physical System using a Hybrid Dynamic Bayes Net
Uri Lerner , Brooks Moses , Maricia Scott , Sheila McIlraith , Daphne Koller
On the Construction of the Inclusion Boundary Neighbourhood for Markov Equivalence Classes of Bayesian Network Structures
Vincent Auvray , Louis Wehenkel
On the Testable Implications of Causal Models with Hidden Variables
Jin Tian , Judea Pearl
Optimal Time Bounds for Approximate Clustering
Ramgopal Mettu , Greg Plaxton
Particle Filters in Robotics (Invited Talk)
Sebastian Thrun
Planning under Continuous Time and Resource Uncertainty: A Challenge for AI
John Bresina , Richard Dearden , Nicolas Meuleau , Sailesh Ramkrishnan , David Smith , Richard Washington
Polynomial Value Iteration Algorithms for Detrerminstic MDPs
Omid Madani
Qualitative MDPs and POMDPs: An Order-Of-Magnitude Approximation
Blai Bonet , Judea Pearl
Real-Time Inference with Large-Scale Temporal Bayes Nets
Masami Takikawa , Bruce D'Ambrosio , Ed Wright
Real-valued All-Dimensions search: Low-overhead rapid searching over subsets of attributes
Andrew Moore , Jeff Schneider
Reasoning about Expectation
Joseph Halpern , Riccardo Pucella
Reduction of Maximum Entropy Models to Hidden Markov Models
Joshua Goodman
Reinforcement Learning with Partially Known World Dynamics
Christian Shelton
Robust Feature Selection by Mutual Information Distributions
Marco Zaffalon , Marcus Hutter
Staged Mixture Modelling and Boosting
Christopher Meek , Bo Thiesson , David Heckerman
Statistical Decisions Using Likelihood Information Without Prior Probabilities
Phan Giang , Prakash Shenoy
The Thing That We Tried Didn't Work Very Well : Deictic Representation in Reinforcement Learning
Sarah Finney , Natalia Gardiol , Leslie Kaelbling , Tim Oates
Tree-dependent Component Analysis
Francis Bach , Michael Jordan
Unconstrained Influence Diagrams
Finn Jensen , Marta Vomlelova
Unsupervised Active Learning in Large Domains
Harald Steck , Tommi Jaakkola
Updating Probabilities
Peter Grunwald , Joseph Halpern
Value Function Approximation in Zero-Sum Markov Games
Michail Lagoudakis , Ron Parr

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