Uncertainty in Artificial Intelligence
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Proceedings of the Seventeenth Conference Conference on Uncertainty in Artificial Intelligence ( 2001 )
Aug 2-5 2001, Seattle, WA

Edited By:
John Breese, Daphne Koller
Published By: Morgan Kaufmann, San Francisco, CA
ISBN:  1-55860-800-1

A Bayesian Approach to Tackling Hard Computational Problems
Eric Horvitz , Yongshao Ruan , Carla Gomes , Henry Kautz , Bart Selman , David Chickering
A Bayesian Multiresolution Independence Test for Continuous Variables
Dimitris Margaritis , Sebastian Thrun
A Calculus for Causal Relevance
Blai Bonet
A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application
Ann Nicholson , Tal Boneh , Tim Wilkin , Kaye Stacey , Liz Sonenberg , Vicki Steinle
A Clustering Approach to Solving Large Stochastic Matching Problems
Milos Hauskrecht , Eli Upfal
A Comparison of Axiomatic Approaches to Qualitative Decision Making Using Possibility Theory
Phan Giang , Prakash Shenoy
A Dynamic Programming Model for Determining Bidding Strategies in Sequential Auctions: Quasi-linear Utility and Budget Constraints
Hiromitsu Hattori , Makoto Yokoo , Yuko Sakurai , Toramatsu Shintani
A Factorized Variational Technique for Phase Unwrapping in Markov Random Fields
Kannan Achan , Brendan Frey , Ralf Koetter
A Logic for Reasoning about Upper Probabilities
Joseph Halpern , Riccardo Pucella
A Mixed Graphical Model for Rhythmic Parsing
Christopher Raphael
A Tractable POMDP for a Class of Sequencing Problems
Paat Rusmevichientong , Benjamin van Roy
Aggregating Learned Probabilistic Beliefs
Pedrito Maynard-Reid II , Urszula Chajewska
Analysing Sensitivity Data from Probabilistic Networks
Linda van der Gaag , Silja Renooij
Approximating MAP using Local Search
James Park , Adnan Darwiche
Bayesian Error-Bars for Belief Net Inference
Tim Van Allen , Russell Greiner , Peter Hooper
Belief Optimization for Binary Networks: A Stable Alternative to Loopy Belief Propagation
Max Welling , Yee Whye Teh
Causal Discovery from Changes
Jin Tian , Judea Pearl
Causes and Explanations: A Structural-Model Approach --- Part 1: Causes
Joseph Halpern , Judea Pearl
Classifier Learning with Supervised Marginal Likelihood
Petri Kontkanen , Petri Myllymaki , Henry Tirri
Conditions Under Which Conditional Independence and Scoring Methods Lead to Identical Selection of Bayesian Network Models
Robert Cowell
Confidence Inference in Bayesian Networks
Jian Cheng , Marek Druzdzel
Cross-covariance modelling via DAGs with hidden variables
Jacob Wegelin , Thomas Richardson
Decision-Theoretic Planning with Concurrent Temporally Extended Actions
Khashayar Rohanimanesh , Sridhar Mahadevan
Direct and Indirect Effects
Judea Pearl
Discovering Multiple Constraints that are Frequently Approximately Satisfied
Geoffrey Hinton , Yee Whye Teh
Efficient Approximation for Triangulation of Minimum Treewidth
Eyal Amir
Efficient Stepwise Selection in Decomposable Models
Amol Deshpande , Minos Garofalakis , Michael Jordan
Enumerating Markov Equivalence Classes of Acyclic Digraph Models
Steven Gillispie , Michael Perlman
Estimating Well-Performing Bayesian Networks using Bernoulli Mixtures
Geoff Jarrad
Exact Inference in Networks with Discrete Children of Continuous Parents
Uri Lerner , Eran Segal , Daphne Koller
Expectation Propagation for approximate Bayesian inference
Thomas Minka
Graphical Models for Game Theory
Michael Kearns , Michael Littman , Satinder Singh
Graphical readings of possibilistic logic bases
Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade
Hybrid Processing of Beliefs and Constraints
Rina Dechter , David Larkin
Hypothesis Management in Situation-Specific Network Construction
Kathryn Laskey , Suzanne Mahoney , Ed Wright
Improved learning of Bayesian networks
Tomas Kocka , Robert Castelo
Incorporating Expressive Graphical Models in Variational Approximations: Chain-Graphs and Hidden Variables
Tal El-Hay , Nir Friedman
Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms
Uri Lerner , Ron Parr
Instrumentality Tests Revisited
Blai Bonet
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
John Lafferty , Larry Wasserman
Lattice Particle Filters
Dirk Ormoneit , Christiane Lemieux , David Fleet
Learning the Dimensionality of Hidden Variables
Gal Elidan , Nir Friedman
Linearity Properties of Bayes Nets with Binary Variables
David Danks , Clark Glymour
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure
Nicos Angelopoulos , James Cussens
Maximum Likelihood Bounded Tree-Width Markov Networks
Nathan Srebro
Multivariate Information Bottleneck
Nir Friedman , Ori Mosenzon , Noam Slonim , Naftali Tishby
On characterizing Inclusion of Bayesian Networks
Tomas Kocka , Remco Bouckaert , Milan Studeny
Planning and Acting under Uncertainty: A New Model for Spoken Dialogue Systems
Bo Zhang , Qingsheng Cai , Jianfeng Mao , Baining Guo
Plausible reasoning from spatial observations
Jerome Lang , Philippe Muller
Policy Improvement for POMDPs Using Normalized Importance Sampling
Christian Shelton
Pre-processing for Triangulation of Probabilistic Networks
Hans Bodlaender , Arie Koster , Frank van den Eijkhof , Linda van der Gaag
Probabilistic Logic Programming under Inheritance with Overriding
Thomas Lukasiewicz
Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments
Alexandrin Popescul , Lyle Ungar , David Pennock , Steve Lawrence
Recognition Networks for Approximate Inference in BN20 Networks
Quaid Morris
Robust Combination of Local Controllers
Carlos Guestrin , Dirk Ormoneit
Semi-Instrumental Variables: A Test for Instrument Admissibility
Tianjiao Chu , Richard Scheines , Peter Spirtes
Similarity Measures on Preference Structures, Part II: Utility Functions
Vu Ha , Peter Haddawy , John Miyamoto
Solving Influence Diagrams using HUGIN, Shafer-Shenoy and Lazy Propagation
Anders Madsen , Dennis Nilsson
Statistical Modeling in Continuous Speech Recognition (CSR)(Invited Talk)
Steve Young
Sufficiency, Separability and Temporal Probabilistic Models
Avi Pfeffer
Symmetric Collaborative Filtering Using the Noisy Sensor Model
Rita Sharma , David Poole
The Factored Frontier Algorithm for Approximate Inference in DBNs
Kevin Murphy , Yair Weiss
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
Lex Weaver , Nigel Tao
Toward General Analysis of Recursive Probability Models
Daniel Pless , George Luger
UCP-Networks: A Directed Graphical Representation of Conditional Utilities
Craig Boutilier , Fahiem Bacchus , Ronen Brafman
Using Bayesian Networks to Identify the Causal Effect of Speeding in Individual Vehicle/Pedestrian Collisions
Gary Davis
Using Temporal Data for Making Recommendations
Andrew Zimdars , David Chickering , Christopher Meek
Value-Directed Sampling Methods for POMDPs
Pascal Poupart , Luis Ortiz , Craig Boutilier
Variational MCMC
Nando de Freitas , Pedro Hojen-Sorensen , Michael Jordan , Stuart Russell
Vector-space Analysis of Belief-state Approximation for POMDPs
Pascal Poupart , Craig Boutilier
When do Numbers Really Matter?
Hei Chan , Adnan Darwiche

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