UAI 2004 Schedule
Wednesday, July 7: Applications Workshop
Thursday, July 8: Tutorials
8:30 |
Eliciting, Modeling, and Reasoning about Preference using CP-nets |
Ronen Brafman, Ben-Gurion University | |
Download Slides | |
10:10 | Break |
10:30 | Constraint processing: a graphical models perspective |
Rina Dechter, University of California at Irvine | |
Download Slides | |
12:10 | Lunch |
1:50 | Graphical Models in Computational Molecular Biology |
Nir Friedman, Hebrew University | |
Download Slides Part I | |
Download Slides Part II | |
Download Slides Part IIII | |
3:30 | Break |
3:50 | Graphical models, exponential families, and variational inference |
Martin Wainwright, University of California at Berkeley | |
Download Slides | |
5:30 | Adjourn |
6:30 | Reception |
Friday, July 9
8:30 |
Welcome |
8:50 | Session: Foundations |
Robustness of Causal Claims | |
Judea Pearl | |
Monotonicity in Bayesian Networks | |
Linda van der Gaag, Hans Bodlaender, Ad Feelders | |
A new characterization of probabilities in Bayesian networks | |
Lenhart Schubert | |
The Case-Factor Complexity of Markov Random Fields | |
David McAllester, Michael Collins, Fernando Pereira | |
10:30 | Break |
11:00 | Invited Talk: Cascading Behavior and Bursty Dynamics in Computational Models of Social Networks |
Jon Kleinberg | |
12:00 | Lunch |
1:40 | Session: Probabilistic Modeling I |
Hybrid Influence Diagrams Using Mixtures of Truncated Exponentials | |
Barry Cobb, Prakash Shenoy | |
The Author-Topic Model for Authors and Documents | |
Michal Rosen-Zvi, Thomas Griffiths, Mark Steyvers, Padhraic Smyth | |
2:30 | Invited Talk: Markov Processes and Markov Decision Processes: The Verification Perspective |
Moshe Vardi | |
3:30 | Poster Highlights |
4:15 | Poster Session I |
Saturday, July 10
8:30 |
Invited Talk: What is the matter? Explorations in text categorization |
Lillian Lee | |
9:30 | Session: Multiple Agents |
Reputation Systems: An Axiomatic Approach | |
Moshe Tennenholtz | |
Regret Minimizing Equilibria and Mechanisms for Games with Strict Type Uncertainty | |
Nathanael Hyafil, Craig Boutilier | |
10:20 | Break |
10:50 | Session: Temporal Models |
Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences | |
Cosma Shalizi, Kristina Shalizi | |
Conditional Chow-Liu Tree Structures for Modeling Discrete-Valued Vector Time Series | |
Sergey Kirshner, Padhraic Smyth, Andrew Robertson | |
ARMA Time-Series Modeling with Graphical Models | |
Bo Thiesson, Max Chickering, David Heckerman, Christopher Meek | |
12:05 | Lunch |
2:00 | Session: Non-probabilistic Reasoning |
An axiomatic framework for order of magnitude confidence relations | |
Didier Dubois, Helene Fargier | |
A Logic Programming Framework for Possibilistic Argumentation with Vague Knowledge | |
Carlos Chesnevar, Guillermo Simari, Teresa Alsinet, Lluis Godo | |
Using arguments for making decisions: A possibilistic logic approach | |
Leila Amgoud, Henri Prade | |
3:15 | Poster Highlights |
4:00 | Poster Session II |
7:30 | Banquet |
Talk: Bayesian or Frequentist? How to Double Your Chances for a Date. | |
Ed George |
Sunday, July 11
8:30 |
Invited Talk: Good-Turing estimation and its applications |
Alon Orlitsky | |
9:30 | Session: Inference |
Breaking the Loops: An Efficient MCMC Method for Markov Random Fields | |
Firas Hamze, Nando de Freitas | |
Annealed MAP | |
Changhe Yuan, Tsai-Ching Lu, Marek Druzdzel | |
10:20 | Break |
10:50 | Session: Learning |
"Ideal Parent" Structure Learning for Continuous Variable Networks | |
Gal Elidan, Iftach Nachman, Nir Friedman | |
Active Model Selection | |
Omid Madani, Daniel Lizotte, Russ Greiner | |
PAC-learning bounded tree-width graphical models | |
Mukund Narasimhan, Jeff Bilmes | |
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters | |
Peter Hooper | |
12:30 | Lunch |
2:00 | Session: Decision-theoretic planning |
Metrics for Finite Markov Decision Processes | |
Norman Ferns, Prakash Panangaden, Doina Precup | |
Heuristic Search Value Iteration for POMDPs | |
Trey Smith, Reid Simmons | |
2:50 | Session: Probabilistic Modeling II |
Convolutional factor graphs as probabilistic models | |
Yongyi Mao, Frank Kschischang, Brendan Frey | |
Iterative Conditional Fitting for Gaussian Ancestral Graph Models |
|
Mathias Drton, Thomas Richardson | |
3:40 | Break |
4:10 | Session: Applications |
Bayesian Biosurveillance of Disease Outbreaks | |
Gregory Cooper, Denver Dash, John Levander, Weng-Keen Wong, William Hogan, Michael Wagner | |
Probabilistic index maps for modeling natural signals | |
Nebojsa Jojic, Yaron Caspi, Manual Reyes-Gomez | |
An Integrated, Conditional Model of Information Extraction and Coreference with Application to Citation Matching | |
Benjamin Wellner, Andrew McCallum, Fuchun Peng, Michael Hay |