22. UAI 2006:
Cambridge,
MA,
USA
UAI '06, Proceedings of the 22nd Conference in Uncertainty in Artificial Intelligence, July 13-16 2006, Cambridge, MA, USA.
AUAI Press 2006, ISBN 0-9749039-2-2 BibTeX
- Manfred K. Warmuth:
A Bayesian Probability Calculus for Density Matrices.
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- Manfred K. Warmuth, Dima Kuzmin:
A Bayesian Probability Calculus for Density Matrices.
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- Bhaskara Marthi, Stuart J. Russell, David Andre:
A Compact, Hierarchical Q-function Decomposition.
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- Sanjoy Dasgupta, Daniel Hsu, Nakul Verma:
A Concentration Theorem for Projections.
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- Phan Hong Giang:
A New Axiomatization for Likelihood Gambles.
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- Frank Wood, Thomas L. Griffiths, Zoubin Ghahramani:
A Non-Parametric Bayesian Method for Inferring Hidden Causes.
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- David Stavens, Sebastian Thrun:
A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving.
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- Tomi Silander, Petri Myllymäki:
A Simple Approach for Finding the Globally Optimal Bayesian Network Structure.
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- Subramani Mani, Gregory F. Cooper, Peter Spirtes:
A Theoretical Study of Y Structures for Causal Discovery.
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- Arthur Choi, Adnan Darwiche:
A Variational Approach for Approximating Bayesian Networks by Edge Deletion.
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- Joseph Ramsey, Jiji Zhang, Peter Spirtes:
Adjacency-Faithfulness and Conservative Causal Inference.
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- Mikko Koivisto:
Advances in Exact Bayesian Structure Discovery in Bayesian Networks.
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- Michael L. Littman, Nishkam Ravi, Arjun Talwar, Martin Zinkevich:
An Efficient Optimal-Equilibrium Algorithm for Two-player Game Trees.
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- Yaxin Bi, Jiwen Guan:
An Efficient Triplet-based Algorithm for Evidential Reasoning.
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- Varsha Dani, Omid Madani, David M. Pennock, Sumit K. Sanghai, Brian Galebach:
An Empirical Comparison of Algorithms for Aggregating Expert Predictions.
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- Avi Pfeffer:
Approximate Separability for Weak Interaction in Dynamic Systems.
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- Vanessa Didelez:
Asymmetric Separation for Local Independence Graphs.
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- Paul Weng:
Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility.
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- Ricardo Silva, Zoubin Ghahramani:
Bayesian Inference for Gaussian Mixed Graph Models.
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- Zhihua Zhang, Michael I. Jordan:
Bayesian Multicategory Support Vector Machines.
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- Max Welling, Sridevi Parise:
Bayesian Random Fields: The Bethe-Laplace Approximation.
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- Andres Madsen:
Belief Update in CLG Bayesian Networks With Lazy Propagation.
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- Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin:
Chi-square Tests Driven Method for Learning the Structure of Factored MDPs.
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- Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman:
Continuous Time Markov Networks.
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- Yuhong Guo, Dale Schuurmans:
Convex Structure Learning for Bayesian Networks: Polynomial Feature Selection and Approximate Ordering.
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- Bozhena Bidyuk, Rina Dechter:
Cutset Sampling with Likelihood Weighting.
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- Nir Friedman, Raz Kupferman:
Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks.
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- Vanessa Didelez, A. Philip Dawid, Sara Geneletti:
Direct and Indirect Effects of Sequential Treatments.
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- Koby Crammer, Amir Globerson:
Discriminative Learning via Semidefinite Probabilistic Models.
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- Monika Schaeffer, Ronald Parr:
Efficient Selection of Disambiguating Actions for Stereo Vision.
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- Dongryeol Lee, Alexander G. Gray:
Faster Gaussian Summation: Theory and Experiment.
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- Michael Eichler:
Fitting Graphical Interaction Models to Multivariate Time Series.
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- Cédric Pralet, Thomas Schiex, Gérard Verfaillie:
From Influence Diagrams to Multi-operator Cluster DAGs.
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- Matthew J. Beal, Praveen Krishnamurthy:
Gene Expression Time Course Clustering with Countably Infinite Hidden Markov Models.
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- Brian Milch, Stuart J. Russell:
General-Purpose MCMC Inference over Relational Structures.
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- Ian Porteous, Alex Ihter, Padhraic Smyth, Max Welling:
Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation.
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- Carlos Brito, Judea Pearl:
Graphical Condition for Identification in recursive SEM.
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- Ilya Shpitser, Judea Pearl:
Identification of Conditional Interventional Distributions.
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- José M. Peña, Roland Nilsson, Johan Björkegren, Jesper Tegnér:
Identifying the Relevant Nodes Without Learning the Model.
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- Alexander L. Strehl, Lihong Li, Michael L. Littman:
Incremental Model-based Learners With Formal Learning-Time Guarantees.
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- Changsung Kang, Jin Tian:
Inequality Constraints in Causal Models with Hidden Variables.
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- Prakash P. Shenoy:
Inference in Hybrid Bayesian Networks Using Mixtures of Gaussians.
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- Zhao Xu, Volker Tresp, Kai Yu, Hans-Peter Kriegel:
Infinite Hidden Relational Models.
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- Chalee Asavathiratham:
Linear Algebra Approach to Separable Bayesian Networks.
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- Robert G. Cowell, Steffen L. Lauritzen, Julia Mortera:
MAIES: A Tool for DNA Mixture Analysis.
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- Inmar Givoni, Vincent Cheung, Brendan J. Frey:
Matrix Tile Analysis.
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- Iain Murray, Zoubin Ghahramani, David MacKay:
MCMC for Doubly-intractable Distributions.
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- Norm Ferns, Pablo Samuel Castro, Doina Precup, Prakash Panangaden:
Methods for Computing State Similarity in Markov Decision Processes.
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- Chris Bartels, Jeff A. Bilmes:
Non-Minimal Triangulations for Mixed Stochastic/Deterministic Graphical Models.
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- Or Zuk, Shiri Margel, Eytan Domany:
On the Number of Samples Needed to Learn the Correct Structure of a Bayesian Network.
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- Hei Chan, Adnan Darwiche:
On the Robustness of Most Probable Explanations.
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- Ruggiero Cavallo, David C. Parkes, Satinder P. Singh:
Optimal Coordinated Planning Amongst Self-Interested Agents with Private State.
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- Yimin Huang, Marco Valtorta:
Pearl's Calculus of Intervention Is Complete.
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- Scott Sanner, Craig Boutilier:
Practical Linear Value-approximation Techniques for First-order MDPs.
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- John Langford, Roberto Oliveira, Bianca Zadrozny:
Predicting Conditional Quantiles via Reduction to Classification.
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- Kathryn B. Laskey, Ning Xu, Chun-Hung Chen:
Propagation of Delays in the National Airspace System.
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- Harald Steck:
Ranking by Dependence - A Fair Criteria.
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- Seunghwan Lee:
Reasoning about Uncertainty in Metric Spaces.
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- Amar Subramanya, Alvin Raj, Jeff A. Bilmes, Dieter Fox:
Recognizing Activities and Spatial Context Using Wearable Sensors.
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- Gal Elidan, Ian McGraw, Daphne Koller:
Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing.
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- Itai Ashlagi, Moshe Tennenholtz, Dov Monderer:
Robust Learning Equilibrium.
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- Theodore Charitos, Linda C. van der Gaag:
Sensitivity Analysis for Threshold Decision Making with Dynamic Networks.
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- Guy Lebanon:
Sequential Document Representations and Simplicial Curves.
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- Wim Wiegerinck, Bart van den Broek, Bert Kappen:
Stochastic Optimal Control in Continuous Space-Time Multi-Agent Systems.
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- Manabu Kuroki, Zhihong Cai:
Stratified Analysis of 'Probabilities of Causation'.
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- Vikash K. Mansinghka, Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum:
Structured Priors for Structure Learning.
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- Manfred Jaeger:
The AI&M Procedure for Learning from Incomplete Data.
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- Edward Snelson, Zoubin Ghahramani:
Variable Noise and Dimensionality Reduction for Sparse Gaussian processes.
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- Guobiao Mei, Peter Russo:
Visualization of Collaborative Data.
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Copyright © Sat May 16 23:44:08 2009
by Michael Ley (ley@uni-trier.de)