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UAI 200521st Conference on
Uncertainty in Artificial Intelligence
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July 26th-
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On the Value of Correlation
Itai Ashlagi, Dov Monderer and Moshe Tennenholtz
Ordering-based Search: A Simple
and Effective Algorithm for Learning Bayesian Networks
Marc Teyssier and Daphne Koller
A Transformational
Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent
Variables
Jiji Zhang and Peter Spirtes
On Privacy-preserving Histograms
Shuchi Chawla, Cynthia Dwork, Frank McSherry and Kunal Talwar
Metrics for Markov Decision
Processes with Infinite State Spaces
Norman F. Ferns, Prakash Panangaden and Doina Precup
On the Number of Experiments
sufficient and in the worst wase necessary to identify all Causal Relations
among N Variables
Frederick Eberhardt, Clark Glymour and Richard Scheines
Cliquewise Training for
Undirected Models
Charles Sutton and Andrew McCallum
Modifying Bayesian Networks by
Probability Constraints
Yun Peng and Zhongli Ding
Two-way Latent Grouping Model
for User Preference Prediction
Eerika Savia, Kai Puolamäki, Janne Sinkkonen and Samuel
Kaski
Learning Bayesian Network
Parameters with Prior Knowledge about Context-Specific Qualitative Influences.
Ad Feelders and Linda C. van der Gaag
Graphical Identifications for
Total Effects by using Surrogate Variables
Manabu Kuroki, Zhihong Cai and Hiroki Motogaito
MAA*: A Heuristic Search
Algorithm for Solving Decentralized POMDPS
Daniel Szer, Francois Charpillet, Shlomo Zilberstein
Asynchronous Dynamic Bayesian
Networks
Avi Pfeffer and Terry Tai
Maximum Margin Bayesian Networks
Yuhong Guo, Dana Wilkinson and Dale Schuurmans
Learning to Classify Individuals
Based on Group Statistics
Hendrik Kuck and Nando de Freitas
Planning in POMDPS using
Multiplicity Automata
Eyal Even-Dar and Sham M. Kakade and Yishay Mansour
Stable Independence in Perfect
Maps
Peter de Waal and Linda C. van der Gaag
Description Logics with Fuzzy
Concrete Domains
Umberto Straccia
On Bayesian Network
Approximation by Edge Deletion
Arthur Choi, Hei Chan and Adnan Darwiche
Importance Sampling in Bayesian
Networks: An Influence-based Approximation Strategy for Importance Functions
Changhe Yuan and Marek J. Druzdzel
Qualitative Decision Making
under Possibilistic Uncertainty: toward more Discriminant Criteria
Paul Weng
A Model for Reasoning with
Uncertain Rules in Event Composition Systems
Segev Wasserkrug, Avigdor Gal and Opher Etzion
Bounding the Uncertainty of
Graphical Games: The Complexity of Simple Requirements, Pareto and Strong Nash
Equilibria
Gianluigi Greco and Francesco Scarcello
Unsupervised Activity Discovery
and Characterization from Event-Streams
Raffay Hamid, Siddhartha Maddi, Amos Johnson, Aaron Bobick, Irfan Essa, and
Charles Isbell
Cost Sensitive Reachability
Heuristics for Handling State Uncertainty
Daniel Bryce and Subbarao Kambhampati
A Function Approximation
Approach to Estimation of Policy Gradient for POMDP with Structured Policies
Huizhen Yu
A Differential Semantics of Lazy
AR Propagation
Anders L Madsen
Modeling Transportation Routines
using Hybrid Dynamic Mixed Networks
Vibhav Gogate, Rina Dechter, Bozhena Bidyuk, Craig Rindt and James Marca
Local Markov Property for Models
Satisfying Composition Axiom
Changsung Kang and Jin Tian
The Relationship between AND/OR
Search Spaces And Variable Elimination
Robert Mateescu and Rina Dechter
A Heuristic Search Algorithm for
Solving First-Order MDPS
Eldar Karabaev and Olga Skvortsova
A Unified Setting for Inference
and Decision: an Argumentation-based approach
Leila Amgoud
Towards Characterizing Markov
Equivalence Classes for Directed Acyclic Graph Models with Latent Variables
R. Ayesha Ali, Thomas S. Richardson, Peter Spirtes and Jiji Zhang
Nonparametric Bayesian Logic
Peter Carbonetto, Jacek Kisynski, Nando de Freitas and David Poole
Exploiting Evidence-dependent
Sensitivity Bounds
Silja Renooij, Linda C. van der Gaag
Bayes Blocks: An Implementation
of the Variational Bayesian Building Blocks Framework
Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, and Juha Karhunen
Approximate Linear Programming
for First-Order MDPS
Scott Sanner and Craig Boutilier
Counterexample-guided Planning
Krishnendu Chatterjee, Thomas A. Henzinger, Ranjit Jhala, and Rupak
Majumdar
Efficient Algorithm for
Estimation of Qualitative Expected Utility in Possibilistic Case-Based
Reasoning
Jakub Brzostowski and Ryszard Kowalczyk
Existence and Finiteness
Conditions for Risk-Sensitive Planning: Results and Conjectures
Yaxin Liu and Sven Koenig
Generating Markov Equivalent
Maximal Ancestral Graphs by Single Edge Replacement
Jin Tian
A Revision-based Approach to
Resolving Conflicting Information
Guilin Qi, Weiru Liu and David A. Bell
Exploiting Evidence in
Probabilistic Inference
Mark Chavira, David Allen and Adnan Darwiche
Models for Truthful Online
Double Auctions
Jonathan Bredin and David Parkes
Hybrid Bayesian Networks with
Linear Deterministic Variables
Barry R. Cobb and Prakash P. Shenoy
Learning from Sparse Data by
Exploiting Monotonicity Constraints
Eric E. Altendorf, Angelo C. Restificar and Thomas G. Dietterich
Obtaining Calibrated
Probabilities from Boosting
Alexandru Niculescu-Mizil and Rich Caruana
Of Starships and Klingons:
Bayesian Logic for the 23rd Century
Kathryn B. Laskey and Paulo C. G. da Costa
On the Detection of Concept
changes in Time-varying data stream by Testing Exchangeability
Shen-Shyang Ho and Harry Wechsler
Learning Factor Graphs
in Polynomial Time & Sample Complexity
Pieter Abbeel, Daphne Koller and Andrew Y. Ng
Expectation Propagation for
Continuous Time Bayesian Networks
Uri Nodelman, Daphne Koller and Christian R. Shelton
Predictive Linear-Gaussian
Models of Stochastic Dynamical Systems
Matthew Rudary, Satinder Singh, and David Wingate
Self-Confirming Price Prediction
for Bidding in Simultaneous Ascending Auctions
Anna Osepayshvili, Michael P. Wellman, Daniel M. Reeves, and Jeffrey K.
MacKie-Mason
Unsupervised Spectral Learning
Susan Shortreed and Marina Meila
Use of Dempster-Shafer Conflict
Metric to Detect Interpretation Inconsistency
Jennifer Carlson and Robin S. Murphy
Mining Associated Text and
Images with Dual-Wing Harmoniums
Eric P. Xing, Rong Yan and Alexander G. Hauptmann
A submodular-supermodular
Procedure with applications to Discriminative Structure Learning
Mukund Narasimhan and Jeff Bilmes
Approximate Inference Algorithms
for Hybrid Bayesian Networks with Discrete Constraints
Vibhav Gogate and Rina Dechter
Counterfactual Reasoning in
Linear Structural Equation Models
Zhihong Cai and Manabu Kuroki