Uncertainty in Artificial Intelligence
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Proceedings of the Twenty-Fourth Conference Conference on Uncertainty in Artificial Intelligence ( 2008 )
July 9- 12 2008, Helsinki, Finland

Edited By:
David McAllester, Petri Myllymaki
Published By: AUAI Press, Corvallis, Oregon
ISBN: 0-9749039-4-9

A Game-Theoretic Analysis of Updating Sets of Probabilities
Peter Grunwald , Joseph Halpern
A Polynomial-time Nash Equilibrium Algorithm for Repeated Stochastic Games
Enrique Munoz de Cote , Michael Littman
Adaptive Inference on General Graphical Models
Umut Acar , Alexander Ihler , Ramgopal Mettu , Ozgur Sumer
Almost Optimal Intervention Sets for Causal Discovery
Frederick Eberhardt
AND/OR Importance Sampling
Vibhav Gogate , Rina Dechter
Approximating the Partition Function by Deleting and then Correcting for Model Edges
Arthur Choi , Adnan Darwiche
Bayesian network learning by compiling to weighted MAX-SAT
James Cussens
Bayesian Out-Trees
Tony Jebara
Bounding Search Space Size via (Hyper)tree Decompositions
Lars Otten , Rina Dechter
Bounds on the Bethe Free Energy for Gaussian Networks
Botond Cseke , Tom Heskes
Causal discovery of linear acyclic models with arbitrary distributions
Patrik Hoyer , Aapo Hyvarinen , Richard Scheines , Peter Spirtes , Joseph Ramsey , Gustavo Lacerda , Shohei Shimizu
Church: a language for generative models
Noah Goodman , Vikash Mansinghka , Daniel Roy , Keith Bonawitz , Joshua Tenenbaum
Clique Matrices for Statistical Graph Decomposition and Parameterising Restricted Positive Definite Matrices
David Barber
Complexity of Inference in Graphical Models
Venkat Chandrasekaran , Nathan Srebro , Prahladh Harsha
Constrained Approximate Maximum Entropy Learning of Markov Random Fields
Varun Ganapathi , David Vickrey , John Duchi , Daphne Koller
Continuous Time Dynamic Topic Models
Chong Wang , David Blei , David Heckerman
Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies
Tamir Hazan , Amnon Shashua
Convex Point Estimation using Undirected Bayesian Transfer Hierarchies
Gal Elidan , Ben Packer , Geremy Heitz , Daphne Koller
CORL: A Continuous-state Offset-dynamics Reinforcement Learner
Emma Brunskill , Bethany Leffler , Lihong Li , Michael Littman , Nicholas Roy
CT-NOR: Representing and Reasoning About Events in Continuous Time
Aleksandr Simma , Moises Goldszmidt , John MacCormick , Paul Barham , Richard Black , Rebecca Isaacs , Richard Mortier
Cumulative distribution networks and the derivative-sum-product algorithm
Jim Huang , Brendan Frey
Discovering Cyclic Causal Models by Independent Components Analysis
Gustavo Lacerda , Peter Spirtes , Joseph Ramsey , Patrik Hoyer
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping
Richard Sutton , Csaba Szepesvari , Alborz Geramifard , Michael Bowling
Efficient inference in persistent Dynamic Bayesian Networks
Tomas Singliar , Denver Dash
Estimation and Clustering with Infinite Rankings
Marina Meila , Le Bao
Explanation Trees for Causal Bayesian Networks
Ulf Nielsen , Jean-Philippe Pellet , André Elisseeff
Feature Selection via Block-Regularized Regression
Seyoung Kim , Eric Xing
Flexible Priors for Exemplar-based Clustering
Daniel Tarlow , Richard Zemel , Brendan Frey
Gibbs Sampling in Factorized Continuous-Time Markov Processes
Tal El-Hay , Nir Friedman , Raz Kupferman
Greedy Block Coordinate Descent for Large Scale Gaussian Process Regression
Liefeng Bo , Cristian Sminchisescu
Hierarchical POMDP Controller Optimization by Likelihood Maximization
Marc Toussaint , Laurent Charlin , Pascal Poupart
Hybrid Variational/Gibbs Collapsed Inference in Topic Models
Max Welling , Yee Whye Teh , Hilbert Kappen
Identifying Dynamic Sequential Plans
Jin Tian
Identifying Optimal Sequential Decisions
Philip Dawid , Vanessa Didelez
Identifying reasoning patterns in games
Dimitrios Antos , Avi Pfeffer
Improving Gradient Estimation by Incorporating Sensor Data
Gregory Lawrence , Stuart Russell
Improving the Accuracy and Efficiency of MAP Inference for Markov Logic
Sebastian Riedel
Inference for Multiplicative Models
Ydo Wexler , Christopher Meek
Knowledge Combination in Graphical Multiagent Model
Quang Duong , Michael Wellman , Satinder Singh
Latent Topic Models for Hypertext
Amit Gruber , Michal Rosen-Zvi , Yair Weiss
Learning and Solving Many-Player Games through a Cluster-Based Representation
Sevan Ficici , David Parkes , Avi Pfeffer
Learning Arithmetic Circuits
Daniel Lowd , Pedro Domingos
Learning Convex Inference of Marginals
Justin Domke
Learning Hidden Markov Models for Regression using Path Aggregation
Keith Noto , Mark Craven
Learning Inclusion-Optimal Chordal Graphs
Vincent Auvray , Louis Wehenkel
Learning the Bayesian Network Structure: Dirichlet Prior versus Data
Harald Steck
Learning When to Take Advice: A Statistical Test for Achieving A Correlated Equilibrium
Greg Hines , Kate Larson
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Stephane Ross , Joelle Pineau
Modelling local and global phenomena with sparse Gaussian processes
Jarno Vanhatalo , Aki Vehtari
Multi-View Learning in the Presence of View Disagreement
C. Christoudias , Raquel Urtasun , Trevor Darrell
Multi-View Learning over Structured and Non-Identical Outputs
Kuzman Ganchev , Joao Graca , John Blitzer , Ben Taskar
New Techniques for Algorithm Portfolio Design
Matthew Streeter , Stephen Smith
Observation Subset Selection as Local Compilation of Performance Profiles
Yan Radovilsky , Solomon Shimony
On Identifying Total Effects in the Presence of Latent Variables and Selection bias
Zhihong Cai , Manabu Kuroki
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach
Mathias Niepert , Dirk Van Gucht , Marc Gyssens
Partitioned Linear Programming Approximations for MDPs
Branislav Kveton , Milos Hauskrecht
Projected Subgradient Methods for Learning Sparse Gaussians
John Duchi , Stephen Gould , Daphne Koller
Propagation using Chain Event Graphs
Peter Thwaites , Jim Smith , Robert Cowell
Refractor Importance Sampling
Haohai Yu , Robert van Engelen
Sampling First Order Logical Particles
Hannaneh Hajishirzi , Eyal Amir
Sensitivity analysis for finite Markov chains in discrete time
Gert de Cooman , Filip Hermans , Erik Quaeghebeur
Sensitivity analysis in decision circuits
Debarun Bhattacharjya , Ross Shachter
Small Sample Inference for Generalization Error in Classification Using the CUD Bound
Eric Laber , Susan Murphy
Sparse Stochastic Finite-State Controllers for POMDPs
Eric Hansen
Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions
Alejandro Isaza , Csaba Szepesvari , Vadim Bulitko , Russell Greiner
Strategy Selection in Influence Diagrams using Imprecise Probabilities
Cassio de Campos , Qiang Ji
The Computational Complexity of Sensitivity Analysis and Parameter Tuning
Johan Kwisthout , Linda van der Gaag
The Evaluation of Causal Effects in Studies with an Unobserved Exposure/Outcome Variable: Bounds and Identification
Manabu Kuroki , Zhihong Cai
The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features
Kurt Miller , Thomas Griffiths , Michael Jordan
Tightening LP Relaxations for MAP using Message Passing
David Sontag , Talya Meltzer , Amir Globerson , Tommi Jaakkola , Yair Weiss
Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression
David Mimno , Andrew McCallum
Toward Experiential Utility Elicitation for Interface Customization
Bowen Hui , Craig Boutilier

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