UAI 2003

77 papers

1 Billion Pages = 1 Million Dollars? Mining the Web to Play "Who Wants to Be a Millionaire?" Shyong K. Lam, David M. Pennock, Dan Cosley, Steve Lawrence

A Distance-Based Branch and Bound Feature Selection Algorithm Ari Frank, Dan Geiger, Zohar Yakhini

A Generalized Mean Field Algorithm for Variational Inference in Exponential Families Eric P. Xing, Michael I. Jordan, Stuart Russell

A Linear Belief Function Approach to Portfolio Evaluation Liping Liu, Catherine Shenoy, Prakash P. Shenoy

A Logic for Reasoning About Evidence Joseph Y. Halpern, Riccardo Pucella

A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence Mathias Drton, Thomas S. Richardson

A Possibilistic Handling of Partially Ordered Information Salem Benferhat, Sylvain Lagrue, Odile Papini

A Simple Insight into Iterative Belief Propagation's Success Rina Dechter, Robert Mateescu

Active Collaborative Filtering Craig Boutilier, Richard S. Zemel, Benjamin M. Marlin

An Axiomatic Approach to Robustness in Search Problems with Multiple Scenarios Patrice Perny, Olivier Spanjaard

An Empirical Study of W-Cutset Sampling for Bayesian Networks Bozhena Bidyuk, Rina Dechter

An Importance Sampling Algorithm Based on Evidence Pre-Propagation Changhe Yuan, Marek J. Druzdzel

Approximate Decomposition: A Method for Bounding and Estimating Probabilistic and Deterministic Queries David Larkin

Approximate Inference and Constrained Optimization Tom Heskes, Kees Albers, Bert Kappen

Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models Dmitry Rusakov, Dan Geiger

Bayesian Hierarchical Mixtures of Experts Christopher M. Bishop, Markus Svensén

Boltzmann Machine Learning with the Latent Maximum Entropy Principle Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin Zhao

Budgeted Learning of Naive-Bayes Classifiers Daniel J. Lizotte, Omid Madani, Russell Greiner

CLP(BN): Constraint Logic Programming for Probabilistic Knowledge Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens

Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying Ma, HongJiang Zhang

Cooperative Negotiation in Autonomic Systems Using Incremental Utility Elicitation Craig Boutilier, Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh

Dealing with Uncertainty in Fuzzy Inductive Reasoning Methodology Francisco Mugica, Àngela Nebot, Pilar Gómez

Decentralized Sensor Fusion with Distributed Particle Filters Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian Thrun

Decision Making with Partially Consonant Belief Functions Phan Hong Giang, Prakash P. Shenoy

Efficient Gradient Estimation for Motor Control Learning Gregory Lawrence, Noah J. Cowan, Stuart Russell

Efficient Inference in Large Discrete Domains Rita Sharma, David Poole

Efficient Parametric Projection Pursuit Density Estimation Max Welling, Richard S. Zemel, Geoffrey E. Hinton

Efficiently Inducing Features of Conditional Random Fields Andrew McCallum

Exploiting Locality in Searching the Web Joel Young, Thomas L. Dean

Extending Factor Graphs so as to Unify Directed and Undirected Graphical Models Brendan J. Frey

Implementation and Comparison of Solution Methods for Decision Processes with Non-Markovian Rewards Charles Gretton, David Price, Sylvie Thiébaux

Incremental Compilation of Bayesian Networks M. Julia Flores, José A. Gámez, Kristian G. Olesen

Inference in Polytrees with Sets of Probabilities José Carlos Ferreira da Rocha, Fábio Gagliardi Cozman, Cassio Polpo de Campos

Large-Sample Learning of Bayesian Networks Is NP-Hard David Maxwell Chickering, Christopher Meek, David Heckerman

Layerwidth: Analysis of a New Metric for Directed Acyclic Graphs Mark Hopkins

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

Learning Generative Models of Similarity Matrices Rómer Rosales, Brendan J. Frey

Learning Measurement Models for Unobserved Variables Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes

Learning Module Networks Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman

Learning Riemannian Metrics Guy Lebanon

Locally Weighted Naive Bayes Eibe Frank, Mark A. Hall, Bernhard Pfahringer

Loopy Belief Propagation as a Basis for Communication in Sensor Networks Christopher Crick, Avi Pfeffer

Marginalizing Out Future Passengers in Group Elevator Control Daniel Nikovski, Matthew Brand

Markov Random Walk Representations with Continuous Distributions Chen-Hsiang Yeang, Martin Szummer

Monte Carlo Matrix Inversion Policy Evaluation Fletcher Lu, Dale Schuurmans

Monte-Carlo Optimizations for Resource Allocation Problems in Stochastic Network Systems Milos Hauskrecht, Tomás Singliar

New Advances in Inference by Recursive Conditioning David Allen, Adnan Darwiche

On Information Regularization Adrian Corduneanu, Tommi S. Jaakkola

On Local Optima in Learning Bayesian Networks Jens Dalgaard Nielsen, Tomás Kocka, José M. Peña

On Revising Fuzzy Belief Bases Richard Booth, Eva Richter

On the Convergence of Bound Optimization Algorithms Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani

On Triangulating Dynamic Graphical Models Jeff A. Bilmes, Chris D. Bartels

Optimal Limited Contingency Planning Nicolas Meuleau, David E. Smith

Parametric Dependability Analysis Through Probabilistic Horn Abduction Andrea Bobbio, Stefania Montani, Luigi Portinale

Phase Transition of Tractability in Constraint Satisfaction and Bayesian Network Inference Yong Gao

Policy-Contingent Abstraction for Robust Robot Control Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun

Practically Perfect Christopher Meek, David Maxwell Chickering

Preference-Based Graphic Models for Collaborative Filtering Rong Jin, Luo Si, ChengXiang Zhai

Probabilistic Models for Joint Clustering and Time-Warping of Multidimensional Curves Darya Chudova, Scott Gaffney, Padhraic Smyth

Probabilistic Reasoning About Actions in Nonmonotonic Causal Theories Thomas Eiter, Thomas Lukasiewicz

Reasoning About Bayesian Network Classifiers Hei Chan, Adnan Darwiche

Renewal Strings for Cleaning Astronomical Databases Amos J. Storkey, Nigel C. Hambly, Christopher K. I. Williams, Robert G. Mann

Robust Independence Testing for Constraint-Based Learning of Causal Structure Denver Dash, Marek J. Druzdzel

Solving MAP Exactly Using Systematic Search James D. Park, Adnan Darwiche

Stochastic Complexity of Bayesian Networks Keisuke Yamazaki, Sumio Watanabe

Strong Faithfulness and Uniform Consistency in Causal Inference Jiji Zhang, Peter Spirtes

Structure-Based Causes and Explanations in the Independent Choice Logic Alberto Finzi, Thomas Lukasiewicz

Sufficient Dimensionality Reduction with Irrelevance Statistics Amir Globerson, Gal Chechik, Naftali Tishby

Symbolic Generalization for On-Line Planning Zhengzhu Feng, Eric A. Hansen, Shlomo Zilberstein

Systematic vs. Non-Systematic Algorithms for Solving the MPE Task Radu Marinescu, Kalev Kask, Rina Dechter

The Information Bottleneck EM Algorithm Gal Elidan, Nir Friedman

The Revisiting Problem in Mobile Robot mAP Building: A Hierarchical Bayesian Approach Benjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Konolige

Updating with Incomplete Observations Gert de Cooman, Marco Zaffalon

Upgrading Ambiguous Signs in QPNs Janneke H. Bolt, Silja Renooij, Linda C. van der Gaag

Using the Structure of D-Connecting Paths as a Qualitative Measure of the Strength of Dependence Sanjay Chaudhuri, Thomas Richardson

Value Elimination: Bayesian Interence via Backtracking Search Fahiem Bacchus, Shannon Dalmao, Toniann Pitassi

Web-Based Question Answering: A Decision-Making Perspective David Azari, Eric Horvitz, Susan T. Dumais, Eric Brill