UAI 2008

78 papers

A Bayesian Approach to Learning in Fault Isolation Hannes Wettig, Anna Pernestål, Tomi Silander, Mattias Nyberg

A Game-Theoretic Analysis of Updating Sets of Probabilities Peter Grünwald, Joseph Y. Halpern

A Polynomial-Time Nash Equilibrium Algorithm for Repeated Stochastic Games Enrique Munoz de Cote, Michael L. Littman

Adaptive Inference on General Graphical Models Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu, Özgür Sümer

Almost Optimal Intervention Sets for Causal Discovery Frederick Eberhardt

An Experimental Procedure for Evaluating User-Centered Methods for Rapid Bayesian Network Construction Michael Farry, Jonathan D. Pfautz, Zach Cox, Ann M. Bisantz, R. Stone, Emilie M. Roth

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 O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu

Church: A Language for Generative Models Noah D. Goodman, Vikash K. Mansinghka, Daniel M. Roy, Kallista A. Bonawitz, Joshua B. 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 C. Duchi, Daphne Koller

Continuous Time Dynamic Topic Models Chong Wang, David M. 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, Benjamin Packer, Geremy Heitz, Daphne Koller

CORL: A Continuous-State Offset-Dynamics Reinforcement Learner Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy

CT-NOR: Representing and Reasoning About Events in Continuous Time Aleksandr Simma, Moisés Goldszmidt, John MacCormick, Paul Barham, Richard Black, Rebecca Isaacs, Richard Mortier

Cumulative Distribution Networks and the Derivative-Sum-Product Algorithm Jim C. Huang, Brendan J. Frey

Discovering Cyclic Causal Models by Independent Components Analysis Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer

Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping Richard S. Sutton, Csaba Szepesvári, Alborz Geramifard, Michael H. Bowling

Efficient Inference in Persistent Dynamic Bayesian Networks Tomás Singliar, Denver Dash

Estimation and Clustering with Infinite Rankings Marina Meila, Le Bao

Evaluating Probabilistic Reasoning Systems Adnan Darwiche, Rina Dechter

Explanation Trees for Causal Bayesian Networks Ulf H. Nielsen, Jean-Philippe Pellet, André Elisseeff

Feature Selection via Block-Regularized Regression Seyoung Kim, Eric P. Xing

Flexible Priors for Exemplar-Based Clustering Daniel Tarlow, Richard S. Zemel, Brendan J. 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, Bert Kappen

Hypothesis Management Framework: A Flexible Design Pattern for Belief Networks in Decision Support Systems Sicco Pier van Gosliga, Imelda van de Voorde

Identifying Dynamic Sequential Plans Jin Tian

Identifying Optimal Sequential Decisions A. 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 Models Quang Duong, Michael P. 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 G. Ficici, David C. Parkes, Avi Pfeffer

Learning Arithmetic Circuits Daniel Lowd, Pedro M. 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 vs Data Harald Steck

Learning When to Take Advice: A Statistical Test for Achieving a Correlated Equilibrium Greg Hines, Kate Larson

Methods for Representing Bias in Bayesian Networks Eric Carlson, Sean L. Guarino, Jonathan D. Pfautz

Model-Based Bayesian Reinforcement Learning in Large Structured Domains Stéphane Ross, Joelle Pineau

Modelling Local and Global Phenomena with Sparse Gaussian Processes Jarno Vanhatalo, Aki Vehtari

Multi-View Learning over Structured and Non-Identical Outputs Kuzman Ganchev, João Graça, John Blitzer, Ben Taskar

New Techniques for Algorithm Portfolio Design Matthew J. Streeter, Stephen F. Smith

Observation Subset Selection as Local Compilation of Performance Profiles Yan Radovilsky, Solomon Eyal Shimony

Observations from Field Trials with Several Elicitation Techniques in an Ecological Domain Colette R. Thomas, Ann E. Nicholson, Barry T. Hart

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 C. Duchi, Stephen Gould, Daphne Koller

Propagation Using Chain Event Graphs Peter A. Thwaites, Jim Q. Smith, Robert G. Cowell

Refractor Importance Sampling Haohai Yu, Robert van Engelen

Relieving the Elicitation Burden of Bayesian Belief Networks B. W. Wisse, Sicco Pier van Gosliga, Nicole P. van Elst, Ana Isabel Barros

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 D. Shachter

Small Sample Inference for Generalization Error in Classification Using the CUD Bound Eric B. Laber, Susan A. Murphy

Sparse Stochastic Finite-State Controllers for POMDPs Eric A. Hansen

Speeding up Planning in Markov Decision Processes via Automatically Constructed Abstraction Alejandro Isaza, Csaba Szepesvári, Vadim Bulitko, Russell Greiner

Strategy Selection in Influence Diagrams Using Imprecise Probabilities Cassio P. de Campos, Qiang Ji

The Computational Complexity of Sensitivity Analysis and Parameter Tuning Johan Kwisthout, Linda C. van der Gaag

The Impact of Overconfidence Bias on Practical Accuracy of Bayesian Network Models: An Empirical Study Marek J. Druzdzel, Agnieszka Onisko

The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features Kurt T. Miller, Thomas L. Griffiths, Michael I. Jordan

Tightening LP Relaxations for MAP Using Message Passing David A. Sontag, Talya Meltzer, Amir Globerson, Tommi S. Jaakkola, Yair Weiss

Topic Models Conditioned on Arbitrary Features with Dirichlet-Multinomial Regression David M. Mimno, Andrew McCallum

Toward Experiential Utility Elicitation for Interface Customization Bowen Hui, Craig Boutilier