UAI 2006

68 papers

A Bayesian Probability Calculus for Density Matrices Manfred K. Warmuth, Dima Kuzmin

A Compact, Hierarchical Q-Function Decomposition Bhaskara Marthi, Stuart Russell, David Andre

A Concentration Theorem for Projections Sanjoy Dasgupta, Daniel J. Hsu, Nakul Verma

A New Axiomatization for Likelihood Gambles Phan Hong Giang

A Non-Parametric Bayesian Method for Inferring Hidden Causes Frank D. Wood, Thomas L. Griffiths, Zoubin Ghahramani

A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving David Stavens, Sebastian Thrun

A Simple Approach for Finding the Globally Optimal Bayesian Network Structure Tomi Silander, Petri Myllymäki

A Theoretical Study of Y Structures for Causal Discovery Subramani Mani, Gregory F. Cooper, Peter Spirtes

A Variational Approach for Approximating Bayesian Networks by Edge Deletion Arthur Choi, Adnan Darwiche

Adjacency-Faithfulness and Conservative Causal Inference Joseph D. Ramsey, Jiji Zhang, Peter Spirtes

Advances in Exact Bayesian Structure Discovery in Bayesian Networks Mikko Koivisto

An Efficient Optimal-Equilibrium Algorithm for Two-Player Game Trees Michael L. Littman, Nishkam Ravi, Arjun Talwar, Martin Zinkevich

An Efficient Triplet-Based Algorithm for Evidential Reasoning Yaxin Bi, Jiwen Guan

An Empirical Comparison of Algorithms for Aggregating Expert Predictions Varsha Dani, Omid Madani, David M. Pennock, Sumit K. Sanghai, Brian Galebach

Approximate Separability for Weak Interaction in Dynamic Systems Avi Pfeffer

Asymmetric Separation for Local Independence Graphs Vanessa Didelez

Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility Paul Weng

Bayesian Inference for Gaussian Mixed Graph Models Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani

Bayesian Multicategory Support Vector Machines Zhihua Zhang, Michael I. Jordan

Bayesian Random Fields: The Bethe-Laplace Approximation Max Welling, Sridevi Parise

Belief Update in CLG Bayesian Networks with Lazy Propagation Anders L. Madsen

Chi-Square Tests Driven Method for Learning the Structure of Factored MDPs Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin

Continuous Time Markov Networks Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman

Convex Structure Learning for Bayesian Networks: Polynomial Feature Selection and Approximate Ordering Yuhong Guo, Dale Schuurmans

Cutset Sampling with Likelihood Weighting Bozhena Bidyuk, Rina Dechter

Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks Nir Friedman, Raz Kupferman

Direct and Indirect Effects of Sequential Treatments Vanessa Didelez, A. Philip Dawid, Sara Geneletti

Discriminative Learning via Semidefinite Probabilistic Models Koby Crammer, Amir Globerson

Efficient Selection of Disambiguating Actions for Stereo Vision Monika Schaeffer, Ronald Parr

Faster Gaussian Summation: Theory and Experiment Dongryeol Lee, Alexander G. Gray

Fitting Graphical Interaction Models to Multivariate Time Series Michael Eichler

From Influence Diagrams to Multi-Operator Cluster DAGs Cédric Pralet, Thomas Schiex, Gérard Verfaillie

Gene Expression Time Course Clustering with Countably Infinite Hidden Markov Models Matthew J. Beal, Praveen Krishnamurthy

General-Purpose MCMC Inference over Relational Structures Brian Milch, Stuart Russell

Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation Ian Porteous, Alexander T. Ihler, Padhraic Smyth, Max Welling

Graphical Condition for Identification in Recursive SEM Carlos Brito, Judea Pearl

Identification of Conditional Interventional Distributions Ilya Shpitser, Judea Pearl

Identifying the Relevant Nodes Without Learning the Model José M. Peña, Roland Nilsson, Johan Björkegren, Jesper Tegnér

Incremental Model-Based Learners with Formal Learning-Time Guarantees Alexander L. Strehl, Lihong Li, Michael L. Littman

Inequality Constraints in Causal Models with Hidden Variables Changsung Kang, Jin Tian

Inference in Hybrid Bayesian Networks Using Mixtures of Gaussians Prakash P. Shenoy

Infinite Hidden Relational Models Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel

Linear Algebra Approach to Separable Bayesian Networks Chalee Asavathiratham

MAIES: A Tool for DNA Mixture Analysis Robert G. Cowell, Steffen L. Lauritzen, Julia Mortera

Matrix Tile Analysis Inmar E. Givoni, Vincent Cheung, Brendan J. Frey

MCMC for Doubly-Intractable Distributions Iain Murray, Zoubin Ghahramani, David J. C. MacKay

Methods for Computing State Similarity in Markov Decision Processes Norm Ferns, Pablo Samuel Castro, Doina Precup, Prakash Panangaden

Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models Chris D. Bartels, Jeff A. Bilmes

On the Number of Samples Needed to Learn the Correct Structure of a Bayesian Network Or Zuk, Shiri Margel, Eytan Domany

On the Robustness of Most Probable Explanations Hei Chan, Adnan Darwiche

Optimal Coordinated Planning Amongst Self-Interested Agents with Private State Ruggiero Cavallo, David C. Parkes, Satinder Singh

Pearl's Calculus of Intervention Is Complete Yimin Huang, Marco Valtorta

Practical Linear Value-Approximation Techniques for First-Order MDPs Scott Sanner, Craig Boutilier

Predicting Conditional Quantiles via Reduction to Classification John Langford, Roberto Oliveira, Bianca Zadrozny

Propagation of Delays in the National Airspace System Kathryn B. Laskey, Ning Xu, Chun-Hung Chen

Ranking by Dependence - A Fair Criteria Harald Steck

Reasoning About Uncertainty in Metric Spaces Seunghwan Lee

Recognizing Activities and Spatial Context Using Wearable Sensors Amar Subramanya, Alvin Raj, Jeff A. Bilmes, Dieter Fox

Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing Gal Elidan, Ian McGraw, Daphne Koller

Robust Learning Equilibrium Itai Ashlagi, Moshe Tennenholtz, Dov Monderer

Sensitivity Analysis for Threshold Decision Making with Dynamic Networks Theodore Charitos, Linda C. van der Gaag

Sequential Document Representations and Simplicial Curves Guy Lebanon

Stochastic Optimal Control in Continuous Space-Time Multi-Agent Systems Wim Wiegerinck, Bart van den Broek, Bert Kappen

Stratified Analysis of 'Probabilities of Causation' Manabu Kuroki, Zhihong Cai

Structured Priors for Structure Learning Vikash K. Mansinghka, Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum

The AI&M Procedure for Learning from Incomplete Data Manfred Jaeger

Variable Noise and Dimensionality Reduction for Sparse Gaussian Processes Edward Lloyd Snelson, Zoubin Ghahramani

Visualization of Collaborative Data Guobiao Mei, Peter Russo