UAI 2002

69 papers

A Bayesian Network Scoring Metic That Is Based on Globally Uniform Parameter Priors Mehmet Kayaalp, Gregory F. Cooper

A Constraint Satisfaction Approach to the Robust Spanning Tree Problem with Interval Data Ionut D. Aron, Pascal Van Hentenryck

A New Class of Upper Bounds on the Log Partition Function Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky

Adaptive Foreground and Shadow Detection in Image Sequences Yang Wang, Tele Tan

Advances in Boosting Robert E. Schapire

Almost-Everywhere Algorithmic Stability and Generalization Error Samuel Kutin, Partha Niyogi

An Information-Theoretic External Cluster-Validity Measure Byron Dom

An MDP-Based Recommender System Guy Shani, Ronen I. Brafman, David Heckerman

Anytime State-Based Solution Methods for Decision Processes with Non-Markovian Rewards Sylvie Thiébaux, Froduald Kabanza, John K. Slaney

Asymptotic Model Selection for Naive Bayesian Networks Dmitry Rusakov, Dan Geiger

Bayesian Network Classifiers in a High Dimensional Framework Tatjana Pavlenko, Dietrich von Rosen

Bipolar Possibilistic Representations Salem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade

Causes and Explanations in the Structural-Model Approach : Tractable Cases Thomas Eiter, Thomas Lukasiewicz

CFW: A Collaborative Filtering System Using Posteriors over Weights of Evidence Carl Myers Kadie, Christopher Meek, David Heckerman

Complexity of Mechanism Design Vincent Conitzer, Tuomas Sandholm

Continuation Methods for Mixing Heterogenous Sources Adrian Corduneanu, Tommi S. Jaakkola

Continuous Time Bayesian Networks Uri Nodelman, Christian R. Shelton, Daphne Koller

Coordinates: Probabilistic Forecasting of Presence and Availability Eric Horvitz, Paul Koch, Carl Myers Kadie, Andy Jacobs

Decayed MCMC Filtering Bhaskara Marthi, Hanna Pasula, Stuart Russell, Yuval Peres

Decision Principles to Justify Carnap's Updating Method and to Suggest Corrections Peter P. Wakker

Dimension Correction for Hierarchical Latent Class Models Tomás Kocka, Nevin Lianwen Zhang

Discriminative Probabilistic Models for Relational Data Benjamin Taskar, Pieter Abbeel, Daphne Koller

Distributed Planning in Hierarchical Factored MDPs Carlos Guestrin, Geoffrey J. Gordon

Efficient Nash Computation in Large Population Games with Bounded Influence Michael J. Kearns, Yishay Mansour

Expectation Propogation for Approximate Inference in Dynamic Bayesian Networks Tom Heskes, Onno Zoeter

Expectation-Propogation for the Generative Aspect Model Thomas P. Minka, John D. Lafferty

Exploiting Functional Dependence in Bayesian Network Inference Jirí Vomlel

Factored Particles for Scalable Monitoring Brenda Ng, Leonid Peshkin, Avi Pfeffer

Factorization of Discrete Probability Distributions Dan Geiger, Christopher Meek, Bernd Sturmfels

Finding Optimal Bayesian Networks David Maxwell Chickering, Christopher Meek

Formalizing Scenario Analysis Peter McBurney, Simon Parsons

From Qualitative to Quantitative Probabilistic Networks Silja Renooij, Linda C. van der Gaag

General Lower Bounds Based on Computer Generated Higher Order Expansions Martijn A. R. Leisink, Hilbert J. Kappen

Generalized Instrumental Variables Carlos Brito, Judea Pearl

Inductive Policy Selection for First-Order MDPs Sung Wook Yoon, Alan Fern, Robert Givan

Inference with Seperately Specified Sets of Probabilities in Credal Networks José Carlos Ferreira da Rocha, Fábio Gagliardi Cozman

Interpolating Conditional Density Trees Scott Davies, Andrew W. Moore

Introducing Variable Importance Tradeoffs into CP-Nets Ronen I. Brafman, Carmel Domshlak

IPF for Discrete Chain Factor Graphs Wim Wiegerinck, Tom Heskes

Iterative Join-Graph Propagation Rina Dechter, Kalev Kask, Robert Mateescu

Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun

Learning with Scope, with Application to Information Extraction and Classification David M. Blei, J. Andrew Bagnell, Andrew Kachites McCallum

Loopy Belief Propogation and Gibbs Measures Sekhar Tatikonda, Michael I. Jordan

MAP Complexity Results and Approximation Methods James D. Park

Markov Equivalence Classes for Maximal Ancestral Graphs Ayesha R. Ali, Thomas S. Richardson

Mechanism Design with Execution Uncertainty Ryan Porter, Amir Ronen, Yoav Shoham, Moshe Tennenholtz

Modelling Information Incorporation in Markets, with Application to Detecting and Explaining Events David M. Pennock, Sandip Debnath, Eric J. Glover, C. Lee Giles

Monitoring a Complez Physical System Using a Hybrid Dynamic Bayes Net Uri Lerner, Brooks Moses, Maricia Scott, Sheila A. McIlraith, Daphne Koller

On the Construction of the Inclusion Boundary Neighbourhood for Markov Equivalence Classes of Bayesian Network Structures Vincent Auvray, Louis Wehenkel

On the Testable Implications of Causal Models with Hidden Variables Jin Tian, Judea Pearl

Optimal Time Bounds for Approximate Clustering Ramgopal R. Mettu, C. Greg Plaxton

Particle Filters in Robotics Sebastian Thrun

Planning Under Continuous Time and Resource Uncertainty: A Challenge for AI John L. Bresina, Richard Dearden, Nicolas Meuleau, Sailesh Ramakrishnan, David E. Smith, Richard Washington

Polynomial Value Iteration Algorithms for Detrerminstic MDPs Omid Madani

Qualitative MDPs and POMDPs: An Order-of-Magnitude Approximation Blai Bonet, Judea Pearl

Real-Time Inference with Large-Scale Temporal Bayes Nets Masami Takikawa, Bruce D'Ambrosio, Ed Wright

Real-Valued All-Dimensions Search: Low-Overhead Rapid Searching over Subsets of Attributes Andrew W. Moore, Jeff G. Schneider

Reasoning About Expectation Joseph Y. Halpern, Riccardo Pucella

Reduction of Maximum Entropy Models to Hidden Markov Models Joshua Goodman

Reinforcement Learning with Partially Known World Dynamics Christian R. Shelton

Robust Feature Selection by Mutual Information Distributions Marco Zaffalon, Marcus Hutter

Staged Mixture Modelling and Boosting Christopher Meek, Bo Thiesson, David Heckerman

Statistical Decisions Using Likelihood Information Without Prior Probabilities Phan Hong Giang, Prakash P. Shenoy

The Thing That We Tried Didn't Work Very Well: Deictic Representation in Reinforcement Learning Sarah Finney, Natalia Gardiol, Leslie Pack Kaelbling, Tim Oates

Tree-Dependent Component Analysis Francis R. Bach, Michael I. Jordan

Unconstrained Influence Diagrams Finn Verner Jensen, Marta Vomlelová

Unsupervised Active Learning in Large Domains Harald Steck, Tommi S. Jaakkola

Updating Probabilities Peter Grünwald, Joseph Y. Halpern

Value Function Approximation in Zero-Sum Markov Games Michail G. Lagoudakis, Ronald Parr