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18th Conference on Uncertainty in AI
UAI-2002
Second Call for Participation
August 1-4, 2002
http://www.cs.ucla.edu/~uai02
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Since 1985, the Conference on Uncertainty in Artificial Intelligence
(UAI) has been the primary international forum for presenting new
results on the use of principled methods for reasoning under
uncertainty within intelligent systems. The scope of UAI is wide,
including, but not limited to, representation, automated reasoning,
learning, decision making and knowledge acquisition under
uncertainty.
The 18th Conference on Uncertainty in Artificial Intelligence will be
held in August, 2002 at the University of Alberta, Edmonton, Canada.
The main technical session will be on August 2-4, and will be preceded
with a tutorial program on August 1st. The UAI-2002 venue is in close
proximity to several other conferences, including KDD (July 23-25),
AAAI (July 28 - August 1), and ISMB (August 3-7).
For detailed information about the technical program, schedule, online
registration and accommodations please go to the conference web site at
http://www.cs.ucla.edu/~uai02
Conference Program
******************
The main technical program at UAI-2002 will be from Friday Aug. 2nd
until Sunday Aug. 4th. It will include 66 technical papers that were
selected after a peer-review process. Of these 26 will be given as
plenary presentations, and 40 as poster presentations. The full
program is attached below.
Invited Talks
*************
The following invited speakers will be giving talks at UAI-2002:
* The Problem of Thinking too Much
Persi Diaconis, Stanford University (Banquet speaker)
* Using Statistical Models of Shape in Medical Image Analysis
Eric Grimson, MIT
* Advances in Boosting
Rob Schapire, AT&T
* Particle Filters in Robotics
Sebastian Thrun, CMU
* Decision-Principles to Justify Carnap's Updating Method and
to Suggest Corrections of Probability Judgments
Peter P. Wakker, Maastricht University
Awards
******
We are happy to announce the following paper awards.
Winner of the Best Paper Award:
* A New Class of Upper Bounds on the Log Partition Function
Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky
Winner of the Best Student Paper Award:
* Generalized Instrumental Variables
Carlos Brito, Judea Pearl
Tutorials
*********
The conference will be preceded by a day of advanced tutorials on
Thursday Aug. 1st. This year we have four tutorials:
* Markov Decision Processes
Craig Boutilier, University of Toronto
* Statistical Methods in Natural Language Processing
Michael Collins, AT&T
* Randomization and Rational Decision Making in Optimization
Bart Selman & Carla Gomes, Cornell
* Bayesian Networks for Genetic Linkage Analysis
Dan Geiger, Technion
Registration
************
To register online please go to
http://www.cs.ucla.edu/~uai02/
and select the "Registration" option.
At the conference web site you can find additional information on the
conference location and accommodations.
Note: We cannot guaranty banquet seat for late registration after July
20th.
Conference Organization
***********************
Please direct general inquiries to the General Conference Chair at
koller@cs.stanford.edu. Inquiries about the conference program should
be directed to the Program Co-Chairs at uai02-pchairs@cs.ucla.edu.
General Program Chair:
* Daphne Koller, Stanford. koller@cs.stanford.edu
Program Co-Chairs:
* Adnan Darwiche, UCLA. darwiche@cs.ucla.edu
* Nir Friedman, Hebrew University. nir@cs.huji.ac.il
Conference Schedule
********************
Thursday, August 1st: Tutorials
8:30 Statistical Methods in Natural Language Processing
Michael Collins, AT&T
10:10 Break
10:30 Markov Decision Processes
Craig Boutilier, University of Toronto
12:10 Lunch Break
1:50 Randomization and Rational Decision Making in Optimization
Carla Gomes, Bart Selman, Cornell
3:30 Break
3:50 Bayesian Networks for Genetic Linkage Analysis
Dan Geiger, Technion
5:30 Adjourn
6:00 Reception (Faculty Club)
Friday, August 2nd
8:30 Welcome
8:50 Session: Approximate Inference
A New Class of Upper Bounds on the Log Partition Function
(Best Paper Award)
Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky
Iterative Join-Graph Propagation
Rina Dechter, Kalev Kask, Robert Mateescu
MAP Complexity Results and Approximation Methods
James D. Park
Expectation-Propagation for the Generative Aspect Model
Thomas Minka, John Lafferty
10:30 Break
11:00 Invited Talk
Particle Filters in Robotics
Sebastian Thrun, CMU
12:00 Lunch Break
1:45 Session: Applications
Utility-Directed Pursuit of Preferences in Recommender Systems:
Methods and Experiments
Eric Horvitz, Carl Kadie
Adaptive Foreground and Shadow Detection in Image Sequences
Yang Wang, Tele Tan
Monitoring a Complex Physical System using a Hybrid Dynamic
Bayes Net
Uri Lerner, Brooks Moses, Maricia Scott, Sheila McIlraith,
Daphne Koller
3:00 Poster Highlights
3:40 Poster Session I
7:30 Conference Banquet (Fairmont Hotel Macdonald)
Banquet Talk
The Problem of Thinking too Much
Persi Diaconis, Stanford University
Saturday, August 3rd
8:30 Invited Talk
Using Statistical Models of Shape in Medical Image Analysis
Eric Grimson, MIT
9:30 Session: Learning: Text & Web
Discriminative Probabilistic Models for Relational Data
Ben Taskar, Pieter Abbeel, Daphne Koller
Learning with Scope, with Application to Information Extraction
and Classification
David M. Blei, James A. Bagnell, Andrew K. McCallum
10:20 Break
10:50 Session: Temporal Models
Continuous Time Bayesian Networks
Uri Nodelman, Christian R. Shelton, Daphne Koller
Expectation Propagation for Approximate Inference in Dynamic
Bayesian Networks
Tom Heskes, Onno Zoeter
Decayed MCMC Filtering
Bhaskara Marthi, Hanna Pasula, Stuart Russell, Yuval Peres
Reduction of Maximum Entropy Models to Hidden Markov Models
Joshua Goodman
12:30 Lunch Break
2:00 Session: Multi-agents
Mechanism Design with Execution Uncertainty
Ryan Porter, Amir Ronen, Yoav Shoham, Moshe Tennenholtz
Efficient Nash Computation in Large Population Games with
Bounded Influence
Michael Kearns, Yishay Mansour
2:50 Poster Highlights
3:30 Poster Session II
5:30 Business Meeting
Sunday, August 4th
8:30 Invited Talk
Decision-Principles to Justify Carnap's Updating Method and to
Suggest Corrections of Probability Judgments
Peter P. Wakker, Maastricht University
9:30 Session: Foundations
Generalized Instrumental Variables (Best Student Paper Award)
Carlos Brito, Judea Pearl
Updating Probabilities
Peter D. Grunwald, Joseph Y. Halpern
10:20 Break
10:50 Session: Planning/MDPs
Unconstrained Influence Diagrams
Finn V. Jensen, Marta Vomlelova
Inductive Policy Selection for First-Order Markov Decision
Processes
SungWook Yoon, Alan Fern, Robert Givan
Anytime State-Based Solution Methods for Decision Processes with
non-Markovian Rewards
Sylvie Thiebaux, Froduald Kabanza, John Slaney
Planning Under Continuous Time and Resource Uncertainty: A
Challenge for AI
John Bresina, Richard Dearden, Nicolas Meuleau, Sailesh
Ramakrishnan, David Smith, Rich Washington
12:30 Lunch Break
2:00 Session: Latent Variables
Bayesian Model Selection for Naive Bayes Networks
Dmitry Rusakov, Dan Geiger
On the Testable Implications of Causal Models with Hidden
Variables
Jin Tian, Judea Pearl
2:50 Invited Talk
Advances in Boosting
Rob Schapire, AT&T
3:50 Break
4:15 Session: Learning
Continuation Methods for Mixing Heterogeneous Sources
Adrian Corduneanu, Tommi S. Jaakkola
An Information-Theoretic External Cluster-Validity Measure
Byron E. Dom
Tree-dependent Component Analysis
Francis R. Bach, Michael I. Jordan
5:30 Adjourn
Poster Session I (Friday, August 2nd, 3:40)
Learning Hierarchical Object Maps Of Non-Stationary Environments
With Mobile Robots
Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson
Limketkai, Sebastian Thrun
Qualitative MDPs and POMDPs: An Order-of-Magnitude Approximation
Blai Bonet, Judea Pearl
Complexity of Mechanism Design
Vincent Conitzer, Tuomas Sandholm
Introducing Variable Importance Tradeoffs into CP-Nets
Carmel Domshlak, Ronen I. Brafman
Causes and Explanations in the Structural-Model Approach:
Tractable Cases
Thomas Eiter, Thomas Lukasiewicz
The Thing That We Tried Didn't Work Very Well: Deictic
Representation in Reinforcement Learning
Natalia H. Gardiol, Sarah Finney, Leslie Kaelbling, Tim Oates
Distributed Planning in Hierarchical Factored MDPs
Carlos Guestrin, Geoffrey Gordon
CFW: A Collaborative Filtering System Using Posteriors Over
Weights of Evidence
Carl M. Kadie, Christopher Meek, David Heckerman
A Bayesian Network Scoring Metric That Is Based on Globally
Uniform Parameter Priors
Mehmet Kayaalp, Greg F. Cooper
Almost-everywhere Algorithmic Stability And Generalization Error
Samuel Kutin, Partha Niyogi
Value Function Approximation in Zero-Sum Markov Games
Michail G. Lagoudakis, Ronald Parr
Polynomial Value Iteration Algorithms for Deterministic MDPs
Omid Madani
Staged Mixture Modeling and Boosting
Christopher Meek, Bo Thiesson, David Heckerman
Optimal Time Bounds for Approximate Clustering
Ramgopal R. Mettu, Greg C. Plaxton
Real-valued All-Dimensions search: Low -overhead rapid searching
over subsets of attributes
Andrew W. Moore, Jeff Schneider
Factored Particles for Scalable Monitoring
Brenda Ng, Leonid Peshkin, Avi Pfeffer
Reinforcement Learning with Partially Known World Dynamics
Christian R. Shelton
Unsupervised Active Learning in Large Domains
Harald Steck, Tommi S. Jaakkola
Real-Time Inference with Large-Scale Temporal Bayes Nets
Masami Takikawa, Bruce D'Ambrosio, Ed Wright
Loopy Belief Propagation and Gibbs Measures
Sekhar Tatikonda, Michael I. Jordan
Poster Session II (Saturday, August 3nd, 3:30)
Markov Equivalence Classes for Maximal Ancestral Graphs
Ayesha Ali, Thomas Richardson
A Constraint Satisfaction Approach to the Robust Spanning Tree
with Interval Data
Ionut Aron, Pascal Van Hentenryck
On the Construction of the Inclusion Boundary Neighbourhood for
Markov Equivalence Classes of Bayesian Network Structures
Vincent Auvray, Louis Wehenkel
Bipolar Possibilistic Representations
Salem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade
Finding Optimal Bayesian Networks
Max Chickering, Christopher Meek
Interpolating Conditional Density Trees
Scott Davies, Andrew Moore
Factorization of Discrete Probability Distributions
Dan Geiger, Christopher Meek, Bernd Sturmfels
Statistical Decisions Using Likelihood Information Without Prior
Probabilities
Phan H. Giang, Prakash P. Shenoy
Reasoning About Expectation
Joseph Y. Halpern, Riccardo Pucella
Dimension Correction for Hierarchical Latent Class Models
Tomas Kocka, Nevin L. Zhang
General Lower Bounds based on Computer Generated Higher Order
Expansions
Martijn A.R. Leisink, Hilbert J. Kappen
Formalizing Scenario Analysis
Peter McBurney, Simon Parson
Bayesian Network Classifiers in a High Dimensional Framework
Tatjana Pavlenko, Dietrich von Rosen
Modeling Information Incorporation in Markets, with Application
to Detecting and Explaining Events
David M. Pennock, Sandip Debnath, Eric J. Glover, C. Lee Giles
From Qualitative to Quantitative Probabilistic Networks
Silja Renooij, Linda C. van der Gaag
Inference with Separately Specified Sets of Probabilities in
Credal Networks
Jose Carlos Ferreira da Rocha, Fabio Gagliardi Cozman
An MDP-Based Recommender System
Guy Shani, Ronen Brafman, David Heckerman
Exploiting Functional Dependence in Bayesian Network Inference
Jirka Vomlel
IPF for Discrete Chain Factor Graphs
Wim Wiegerinck, Tom Heskes
Robust Feature Selection by Mutual Information Distributions
Marco Zaffalon, Marcus Hutter
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