Uncertainty in Artificial Intelligence
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Proceedings of the Twenty-Sixth Conference Conference on Uncertainty in Artificial Intelligence ( 2010 )
July 8- 11 2010, Catalina Island, CA

Edited By:
Peter Grunwald, Peter Spirtes
Published By: AUAI Press, Corvallis, Oregon
ISBN: 978-0-9749039-6-5

A Bayesian Matrix Factorization Model for Relational Data
Ajit Singh , Geoffrey Gordon
A Convex Formulation for Learning Task Relationships in Multi-Task Learning
Yu Zhang , Dit-Yan Yeung
A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks
Mathias Niepert
A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models
Miika Pihlaja , Michael Gutmann , Aapo Hyvarinen
A Scalable Method for Solving High-Dimensional Continuous POMDPs Using Local Approximation
Tom Erez , William Smart
ALARMS: Alerting and Reasoning Management System for Next Generation Aircraft Hazards
Alan Carlin , Nathan Schurr , Janusz Marecki
Algorithms and Complexity Results for Exact Bayesian Structure Learning
Sebastian Ordyniak , Stefan Szeider
An Online Learning-based Framework for Tracking
Kamalika Chaudhuri , Yoav Freund , Daniel Hsu
Anytime Planning for Decentralized POMDPs using Expectation Maximization
Akshat Kumar , Shlomo Zilberstein
Approximating Higher-Order Distances Using Random Projections
Ping Li , Michael Mahoney , Yiyuan She
Automated Planning in Repeated Adversarial Games
Enrique Munoz de Cote , Archie Chapman , Adam Sykulski , Nicholas Jennings
Automatic Tuning of Interactive Perception Applications
Qian Zhu , Branislav Kveton , Lily Mummert , Padmanabhan Pillai
Bayesian exponential family projections for coupled data sources
Arto Klami , Seppo Virtanen , Samuel Kaski
Bayesian Inference in Monte-Carlo Tree Search
Gerald Tesauro , V Rajan , Richard Segal
Bayesian Model Averaging Using the k-best Bayesian Network Structures
Jin Tian , Ru He , Lavanya Ram
Bayesian Rose Trees
Charles Blundell , Yee Whye Teh , Katherine Heller
BEEM : Bucket Elimination with External Memory
Kalev Kask , Rina Dechter , Andrew Gelfand
Causal Conclusions that Flip Repeatedly and Their Justification
Kevin Kelly , Conor Mayo-Wilson
Characterizing the Set of Coherent Lower Previsions with a Finite Number of Constraints or Vertices
Erik Quaeghebeur
Combining Spatial and Telemetric Features for Learning Animal Movement Models
Berk Kapicioglu , Robert Schapire , Martin Wikelski , Tamara Broderick
Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker
Farheen Omar , Mathieu Sinn , Jakub Truszkowski , Pascal Poupart , James Tung , Allen Caine
Compiling Possibilistic Networks: Alternative Approaches to Possibilistic Inference
Raouia Ayachi , Nahla Ben Amor , Salem Benferhat , Rolf Haenni
Confounding Equivalence in Causal Inference
Judea Pearl , Azaria Paz
Convergent and Correct Message Passing Schemes for Optimization Problems over Graphical Models
Nicholas Ruozzi , Sekhar Tatikonda
Dirichlet Process Mixtures of Generalized Mallows Models
Marina Meila , Harr Chen
Distribution over Beliefs for Memory Bounded Dec-POMDP Planning
Gabriel Corona , Francois Charpillet
Dynamic programming in in uence diagrams with decision circuits
Ross Shachter , Debarun Bhattacharjya
Efficient Clustering with Limited Distance Information
Konstantin Voevodski , Maria-Florina Balcan , Heiko Roglin , Shang-Hua Teng , Yu Xia
Exact and Approximate Inference in Associative Hierarchical Networks using Graph Cuts
Chris Russell , L'ubor Ladicky , Pushmeet Kohli , Philip Torr
Formula-Based Probabilistic Inference
Vibhav Gogate , Pedro Domingos
Gaussian Process Structural Equation Models with Latent Variables
Ricardo Silva , Robert Gramacy
Gaussian Process Topic Models
Amrudin Agovic , Arindam Banerjee
Gibbs Sampling in Open-Universe Stochastic Languages
Nimar Arora , Rodrigo de Salvo Braz , Erik Sudderth , Stuart Russell
GraphLab: A New Framework For Parallel Machine Learning
Yucheng Low , Joseph Gonzalez , Aapo Kyrola , Danny Bickson , Carlos Guestrin , Joseph Hellerstein
Hybrid Generative/Discriminative Learning for Automatic Image Annotation
Shuang Yang , Jiang Bian , Hongyuan Zha
Identifying Causal Effects with Computer Algebra
Luis Garcia , Sarah Spielvogel , Seth Sullivant
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
Ryan Adams , George Dahl , Iain Murray
Inference by Minimizing Size, Divergence, or their Sum
Sebastian Riedel , David Smith , Andrew McCallum
Inference-less Density Estimation using Copula Bayesian Networks
Gal Elidan
Inferring deterministic causal relations
Povilas Daniusis , Dominik Janzing , Joris Mooij , Jakob Zscheischler , Bastian Steudel , Kun Zhang , Bernhard Schoelkopf
Intracluster Moves for Constrained Discrete-Space MCMC
Firas Hamze , Nando de Freitas
Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery
Kun Zhang , Bernhard Schoelkopf , Dominik Janzing
Irregular-Time Bayesian Networks
Michael Ramati , Yuval Shahar
Learning Game Representations from Data Using Rationality Constraints
Xi Gao , Avi Pfeffer
Learning networks determined by the ratio of prior and data
Maomi Ueno
Learning Structural Changes of Gaussian Graphical Models in Controlled Experiments
Bai Zhang , Yue Wang
Learning Why Things Change: The Difference-Based Causality Learner
Mark Voortman , Denver Dash , Marek Druzdzel
Lifted Inference for Relational Continuous Models
Jaesik Choi , Eyal Amir , David Hill
Matrix Coherence and the Nystrom Method
Ameet Talwalkar , Afshin Rostamizadeh
Maximizing the Spread of Cascades Using Network Design
Daniel Sheldon , Bistra Dilkina , Adam Elmachtoub , Ryan Finseth , Ashish Sabharwal , Jon Conrad , Carla Gomes , David Shmoys , William Allen , Ole Amundsen , William Vaughan
Maximum likelihood fitting of acyclic directed mixed graphs to binary data
Robin Evans , Thomas Richardson
MDPs with Unawareness
Joseph Halpern , Nan Rong , Ashutosh Saxena
Merging Knowledge Bases in Possibilistic Logic by Lexicographic Aggregation
Guilin Qi , Jianfeng Du , Weiru Liu , David Bell
Modeling Events with Cascades of Poisson Processes
Aleksandr Simma , Michael Jordan
Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario
Yan Yan , Romer Rosales , Glenn Fung , Jennifer Dy
Multi-Domain Collaborative Filtering
Yu Zhang , Bin Cao , Dit-Yan Yeung
Negative Tree Reweighted Belief Propagation
Qiang Liu , Alexander Ihler
On a Class of Bias-Amplifying Variables that Endanger Effect Estimates
Judea Pearl
On Measurement Bias in Causal Inference
Judea Pearl
On the Validity of Covariate Adjustment for Estimating Causal Effects
Ilya Shpitser , Tyler VanderWeele , James Robins
Online Semi-Supervised Learning on Quantized Graphs
Michal Valko , Branislav Kveton , Ling Huang , Daniel Ting
Parameter-Free Spectral Kernel Learning
Qi Mao , Ivor Tsang
Parametric Return Density Estimation for Reinforcement Learning
Tetsuro Morimura , Masashi Sugiyama , Hisashi Kashima , Hirotaka Hachiya , Toshiyuki Tanaka
Playing games against nature: optimal policies for renewable resource allocation
Stefano Ermon , Jon Conrad , Carla Gomes , Bart Selman
Possibilistic Answer Set Programming Revisited
Kim Bauters , Steven Schockaert , Martine De Cock , Dirk Vermeir
Prediction with Advice of Unknown Number of Experts
Alexey Chernov , Vladimir Vovk
Primal View on Belief Propagation
Tomas Werner
Probabilistic Similarity Logic
Matthias Brocheler , Lilyana Mihalkova , Lise Getoor
RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains
Emma Brunskill , Stuart Russell
Real-Time Scheduling via Reinforcement Learning
Robert Glaubius , Terry Tidwell , Christopher Gill , William Smart
Regularized Maximum Likelihood for Intrinsic Dimension Estimation
Mithun Das Gupta , Thomas Huang
Risk Sensitive Path Integral Control
Bart van den Broek , Wim Wiegerinck , Hilbert Kappen
Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost
Ping Li
Robust Metric Learning by Smooth Optimization
Kaizhu Huang , Rong Jin , Zenglin Xu , Cheng-Lin Liu
Rollout Sampling Policy Iteration for Decentralized POMDPs
Feng Wu , Shlomo Zilberstein , Xiaoping Chen
Solving Hybrid Influence Diagrams with Deterministic Variables
Yijing Li , Prakash Shenoy
Solving Multistage Influence Diagrams using Branch-and-Bound Search
Changhe Yuan , Xiaojian Wu , Eric Hansen
Source Separation and Higher-Order Causal Analysis of MEG and EEG
Kun Zhang , Aapo Hyvarinen
Sparse-posterior Gaussian Processes for general likelihoods
Yuan (Alan) Qi , Ahmed Abdel-Gawad , Thomas Minka
Speeding up the binary Gaussian process classification
Jarno Vanhatalo , Aki Vehtari
Super-Samples from Kernel Herding
Yutian Chen , Max Welling , Alex Smola
The Cost of Troubleshooting Cost Clusters with Inside Information
Thorsten Ottosen , Finn Jensen
The Hierarchical Dirichlet Process Hidden Semi-Markov Model
Matthew Johnson , Alan Willsky
Three new sensitivity analysis methods for influence diagrams
Debarun Bhattacharjya , Ross Shachter
Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream
Amr Ahmed , Eric Xing
Truthful Feedback for Sanctioning Reputation Mechanisms
Jens Witkowski
Understanding Sampling Style Adversarial Search Methods
Raghuram Ramanujan , Ashish Sabharwal , Bart Selman
Variance-Based Rewards for Approximate Bayesian Reinforcement Learning
Jonathan Sorg , Satinder Singh , Richard Lewis

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