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ORCID18th UAI 2002: Edmonton, Alberta, Canada
- Adnan Darwiche, Nir Friedman:
UAI '02, Proceedings of the 18th Conference in Uncertainty in Artificial Intelligence, University of Alberta, Edmonton, Alberta, Canada, August 1-4, 2002. Morgan Kaufmann 2002, ISBN 1-55860-897-4 - Ayesha R. Ali, Thomas S. Richardson:
Markov Equivalence Classes for Maximal Ancestral Graphs. 1-9 - Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun:
Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots. 10-17 - Ionut D. Aron, Pascal Van Hentenryck:
A Constraint Satisfaction Approach to the Robust Spanning Tree Problem with Interval Data. 18-25 - Vincent Auvray, Louis Wehenkel:
On the Construction of the Inclusion Boundary Neighbourhood for Markov Equivalence Classes of Bayesian Network Structures. 26-35 - Francis R. Bach, Michael I. Jordan:
Tree-dependent Component Analysis. 36-44 - Salem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade:
Bipolar Possibilistic Representations. 45-52 - David M. Blei, J. Andrew Bagnell, Andrew Kachites McCallum:
Learning with Scope, with Application to Information Extraction and Classification. 53-60 - Blai Bonet, Judea Pearl:
Qualitative MDPs and POMDPs: An Order-Of-Magnitude Approximation. 61-68 - Ronen I. Brafman, Carmel Domshlak:
Introducing Variable Importance Tradeoffs into CP-Nets. 69-76 - John L. Bresina, Richard Dearden, Nicolas Meuleau, Sailesh Ramakrishnan, David E. Smith, Richard Washington:
Planning under Continuous Time and Resource Uncertainty: A Challenge for AI. 77-84 - Carlos Brito, Judea Pearl:
Generalized Instrumental Variables. 85-93 - David Maxwell Chickering, Christopher Meek:
Finding Optimal Bayesian Networks. 94-102 - Vincent Conitzer, Tuomas Sandholm:
Complexity of Mechanism Design. 103-110 - Adrian Corduneanu, Tommi S. Jaakkola:
Continuation Methods for Mixing Heterogenous Sources. 111-118 - Scott Davies, Andrew W. Moore:
Interpolating Conditional Density Trees. 119-127 - Rina Dechter, Kalev Kask, Robert Mateescu:
Iterative Join-Graph Propagation. 128-136 - Byron Dom:
An Information-Theoretic External Cluster-Validity Measure. 137-145 - Thomas Eiter, Thomas Lukasiewicz:
Causes and Explanations in the Structural-Model Approach : Tractable Cases. 146-153 - Sarah Finney, Natalia Gardiol, Leslie Pack Kaelbling, Tim Oates:
The Thing that we Tried Didn't Work very Well: Deictic Representation in Reinforcement Learning. 154-161 - Dan Geiger, Christopher Meek, Bernd Sturmfels:
Factorization of Discrete Probability Distributions. 162-169 - Phan Hong Giang, Prakash P. Shenoy:
Statistical Decisions Using Likelihood Information Without Prior Probabilities. 170-178 - Joshua Goodman:
Reduction of Maximum Entropy Models to Hidden Markov Models. 179-186 - Peter Grünwald, Joseph Y. Halpern:
Updating Probabilities. 187-196 - Carlos Guestrin, Geoffrey J. Gordon:
Distributed Planning in Hierarchical Factored MDPs. 197-206 - Joseph Y. Halpern, Riccardo Pucella:
Reasoning about Expectation. 207-215 - Tom Heskes, Onno Zoeter:
Expectation Propogation for Approximate Inference in Dynamic Bayesian Networks. 216-223 - Eric Horvitz, Paul Koch, Carl Myers Kadie, Andy Jacobs:
Coordinates: Probabilistic Forecasting of Presence and Availability. 224-233 - Finn Verner Jensen, Marta Vomlelová:
Unconstrained Influence Diagrams. 234-241 - Carl Myers Kadie, Christopher Meek, David Heckerman:
CFW: A Collaborative Filtering System Using Posteriors over Weights of Evidence. 242-250 - Mehmet Kayaalp, Gregory F. Cooper:
A Bayesian Network Scoring Metic that Is Based on Globally Uniform Parameter Priors. 251-258 - Michael J. Kearns, Yishay Mansour:
Efficient Nash Computation in Large Population Games with Bounded Influence. 259-266 - Tomás Kocka, Nevin Lianwen Zhang:
Dimension Correction for Hierarchical Latent Class Models. 267-274 - Samuel Kutin, Partha Niyogi:
Almost-everywhere Algorithmic Stability and Generalization Error. 275-282 - Michail G. Lagoudakis, Ronald Parr:
Value Function Approximation in Zero-Sum Markov Games. 283-292 - Martijn A. R. Leisink, Hilbert J. Kappen:
General Lower Bounds based on Computer Generated Higher Order Expansions. 293-300 - Uri Lerner, Brooks Moses, Maricia Scott, Sheila A. McIlraith, Daphne Koller:
Monitoring a Complez Physical System using a Hybrid Dynamic Bayes Net. 301-310 - Omid Madani:
Polynomial Value Iteration Algorithms for Detrerminstic MDPs. 311-318 - Bhaskara Marthi, Hanna Pasula, Stuart Russell, Yuval Peres:
Decayed MCMC Filtering. 319-326 - Peter McBurney, Simon Parsons:
Formalizing Scenario Analysis. 327-334 - Christopher Meek, Bo Thiesson, David Heckerman:
Staged Mixture Modelling and Boosting. 335-343 - Ramgopal R. Mettu, C. Greg Plaxton:
Optimal Time Bounds for Approximate Clustering. 344-351 - Thomas P. Minka, John D. Lafferty:
Expectation-Propogation for the Generative Aspect Model. 352-359 - Andrew W. Moore, Jeff G. Schneider:
Real-valued All-Dimensions Search: Low-overhead Rapid Searching over Subsets of Attributes. 360-369 - Brenda Ng, Leonid Peshkin, Avi Pfeffer:
Factored Particles for Scalable Monitoring. 370-377 - Uri Nodelman, Christian R. Shelton, Daphne Koller:
Continuous Time Bayesian Networks. 378-387 - James D. Park:
MAP Complexity Results and Approximation Methods. 388-396 - Tatjana Pavlenko, Dietrich von Rosen:
Bayesian Network Classifiers in a High Dimensional Framework. 397-404 - David M. Pennock, Sandip Debnath, Eric J. Glover, C. Lee Giles:
Modelling Information Incorporation in Markets, with Application to Detecting and Explaining Events. 405-413 - Ryan Porter, Amir Ronen, Yoav Shoham, Moshe Tennenholtz:
Mechanism Design with Execution Uncertainty. 414-421 - Silja Renooij, Linda C. van der Gaag:
From Qualitative to Quantitative Probabilistic Networks. 422-429 - José Carlos Ferreira da Rocha, Fábio Gagliardi Cozman:
Inference with Seperately Specified Sets of Probabilities in Credal Networks. 430-437 - Dmitry Rusakov, Dan Geiger:
Asymptotic Model Selection for Naive Bayesian Networks. 438-445 - Robert E. Schapire:
Advances in Boosting. 446-452 - Guy Shani, Ronen I. Brafman, David Heckerman:
An MDP-based Recommender System. 453-460 - Christian R. Shelton:
Reinforcement Learning with Partially Known World Dynamics. 461-468 - Harald Steck, Tommi S. Jaakkola:
Unsupervised Active Learning in Large Domains. 469-476 - Masami Takikawa, Bruce D'Ambrosio, Ed Wright:
Real-Time Inference with Large-Scale Temporal Bayes Nets. 477-484 - Benjamin Taskar, Pieter Abbeel, Daphne Koller:
Discriminative Probabilistic Models for Relational Data. 485-492 - Sekhar Tatikonda, Michael I. Jordan:
Loopy Belief Propogation and Gibbs Measures. 493-500 - Sylvie Thiébaux, Froduald Kabanza, John K. Slaney:
Anytime State-Based Solution Methods for Decision Processes with non-Markovian Rewards. 501-510 - Sebastian Thrun:
Particle Filters in Robotics. 511-518 - Jin Tian, Judea Pearl:
On the Testable Implications of Causal Models with Hidden Variables. 519-527 - Jirí Vomlel:
Exploiting Functional Dependence in Bayesian Network Inference. 528-535 - Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky:
A New Class of upper Bounds on the Log Partition Function. 536-543 - Peter P. Wakker:
Decision Principles to Justify Carnap's Updating Method and to Suggest Corrections. 544-551 - Yang Wang, Tele Tan:
Adaptive Foreground and Shadow Detection in Image Sequences. 552-559 - Wim Wiegerinck, Tom Heskes:
IPF for Discrete Chain Factor Graphs. 560-567 - Sung Wook Yoon, Alan Fern, Robert Givan:
Inductive Policy Selection for First-Order MDPs. 568-576 - Marco Zaffalon, Marcus Hutter:
Robust Feature Selection by Mutual Information Distributions. 577-584
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