10. UAI 1994: Seattle, Washington, USA

@proceedings{DBLP:conf/uai/1994,
  editor    = {Ramon L{\'o}pez de M{\'a}ntaras and
               David Poole},
  title     = {UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty
               in Artificial Intelligence, July 29-31, 1994, Seattle, Washington,
               USA},
  booktitle = {UAI},
  publisher = {Morgan Kaufmann},
  year      = {1994},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

• Greg Adams, Beth Millar, Eric Neufeld, Tim Philip:
  Ending-based Strategies for Part-of-Speech Tagging. 1-7
  
• Constantin F. Aliferis, Gregory F. Cooper:
  An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets. 8-14
  
• Russ B. Altman, Cheng Che Chen, William B. Poland, Jaswinder Pal Singh:
  Probabilistic Constraint Satisfaction with Non-Gaussian Noise. 15-22
  
• Derek D. Ayers:
  A Bayesian Method Reexamined. 23-27
  
• Adriano Azevedo-Filho, Ross D. Shachter:
  Laplace's Method Approximations for Probabilistic Inference in Belief Networks with Continuous Variables. 28-36
  
• Fahiem Bacchus, Adam J. Grove, Joseph Y. Halpern, Daphne Koller:
  Generating New Beliefs from Old. 37-45
  
• Alexander Balke, Judea Pearl:
  Counterfactual Probabilities: Computational Methods, Bounds and Applications. 46-54
  
• Ildar Z. Batyrshin:
  Modus Ponens Generating Function in the Class of \Lambda-Valuations of Plausibility. 55-59
  
• Ann Becker, Dan Geiger:
  Approximation Algorithms for the Loop Cutset Problem. 60-68
  
• Philippe Besnard, Jérôme Lang:
  Possibility and Necessity Functions over Non-Classical Logics. 69-76
  
• Raj Bhatnagar:
  Exploratory Model Building. 77-85
  
• Edward A. Billard:
  Learning in Multi-Level Stochastic Games with Delayed Information. 86-93
  
• Jim Blythe:
  Planning with External Events. 94-101
  
• Remco R. Bouckaert:
  Properties of Bayesian Belief Network Learning Algorithms. 102-109
  
• Remco R. Bouckaert:
  A Stratified Simulation Scheme for Inference in Bayesian Belief Networks. 110-117
  
• Tom Chávez, Max Henrion:
  Efficient Estimation of the Value of Information in Monte Carlo Models. 119-127
  
• Bruce D'Ambrosio:
  Symbolic Probabilistic Inference in Large BN20 Networks. 128-135
  
• Adnan Darwiche, Moisés Goldszmidt:
  Action Networks: A Framework for Reasoning about Actions and Change under Uncertainty. 136-144
  
• Adnan Darwiche, Moisés Goldszmidt:
  On the Relation between Kappa Calculus and Probabilistic Reasoning. 145-153
  
• Ron Davidson, Michael R. Fehling:
  A Structured, Probabilistic Representation of Action. 154-161
  
• Richard Dearden, Craig Boutilier:
  Integrating Planning and Execution in Stochastic Domains. 162-169
  
• Denise Draper, Steve Hanks:
  Localized Partial Evaluation of Belief Networks. 170-177
  
• Denise Draper, Steve Hanks, Daniel S. Weld:
  A Probablistic Model of Action for Least-Commitment Planning with Information Gathering. 178-186
  
• Marek J. Druzdzel:
  Some Properties of joint Probability Distributions. 187-194
  
• Didier Dubois, Luis Fariñas del Cerro, Andreas Herzig, Henri Prade:
  An Ordinal View of Independence with Application to Plausible Reasoning. 195-203
  
• Florence Dupin de Saint-Cyr, Jérôme Lang, Thomas Schiex:
  Penalty Logic and its Link with Dempster-Shafer Theory. 204-211
  
• Kazuo J. Ezawa:
  Value of Evidence on Influence Diagrams. 212-220
  
• Pascale Fonck:
  Conditional Independence in Possibility Theory. 221-226
  
• Robert M. Fung, Brendan Del Favero:
  Backward Simulation in Bayesian Networks. 227-234
  
• Dan Geiger, David Heckerman:
  Learning Gaussian Networks. 235-243
  
• Dan Geiger, Azaria Paz, Judea Pearl:
  On Testing Whether an Embedded Bayesian Network Represents a Probability Model. 244-252
  
• Robert P. Goldman, Mark S. Boddy:
  Epsilon-Safe Planning. 253-261
  
• Peter Haddawy:
  Generating Bayesian Networks from Probablity Logic Knowledge Bases. 262-269
  
• Peter Haddawy, AnHai Doan:
  Abstracting Probabilistic Actions. 270-277
  
• Petr Hájek, Dagmar Harmancová, Francesc Esteva, Pere Garcia, Lluis Godo:
  On Modal Logics for Qualitative Possibility in a Fuzzy Setting. 278-285
  
• David Heckerman, John S. Breese:
  A New Look at Causal Independence. 286-292
  
• David Heckerman, Dan Geiger, David Maxwell Chickering:
  Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. 293-301
  
• David Heckerman, Ross D. Shachter:
  A Decision-based View of Causality. 302-310
  
• Jochen Heinsohn:
  Probabilistic Description Logics. 311-318
  
• Max Henrion, Gregory M. Provan, Brendan Del Favero, Gillian Sanders:
  An Experimental Comparison of Numerical and Qualitative Probabilistic Reasoning. 319-326
  
• Bernhard Hollunder:
  An Alternative Proof Method for Possibilistic Logic and its Application to Terminological Logics. 327-335
  
• Yen-Teh Hsia:
  Possibilistic Conditioning and Propagation. 336-343
  
• Marcus J. Huber, Edmund H. Durfee, Michael P. Wellman:
  The Automated Mapping of Plans for Plan Recognition. 344-351
  
• Manfred Jaeger:
  A Logic for Default Reasoning About Probabilities. 352-359
  
• Finn Verner Jensen, Frank Jensen:
  Optimal junction Trees. 360-366
  
• Frank Jensen, Finn Verner Jensen, Søren L. Dittmer:
  From Influence Diagrams to junction Trees. 367-373
  
• Uffe Kjærulff:
  Reduction of Computational Complexity in Bayesian Networks Through Removal of Weak Dependences. 374-382
  
• Wai Lam, Fahiem Bacchus:
  Using New Data to Refine a Bayesian Network. 383-390
  
• Jérôme Lang:
  Syntax-based Default Reasoning as Probabilistic Model-based Diagnosis. 391-398
  
• Pat Langley, Stephanie Sage:
  Induction of Selective Bayesian Classifiers. 399-406
  
• Stephane Lapointe, René Proulx:
  Fuzzy Geometric Relations to Represent Hierarchical Spatial Information. 407-415
  
• Paul E. Lehner, Chris Elsaesser, Scott A. Musman:
  Constructing Belief Networks to Evaluate Plans. 416-422
  
• Todd Michael Mansell, Grahame B. Smith:
  Operator Selection While Planning Under Uncertainty. 423-431
  
• Wolfgang Nejdl, Johann Gamper:
  Model-based Diagnosis with Qualitative Temporal Uncertainty. 432-439
  
• Keung-Chi Ng, Tod S. Levitt:
  Incremental Dynamic Construction of Layered Polytree Networks. 440-446
  
• Daniel E. O'Leary:
  Models of Consensus for Multiple Agent Systems. 447-453
  
• Judea Pearl:
  A Probabilistic Calculus of Actions. 454-462
  
• Stephen G. Pimentel, Lawrence M. Brem:
  Robust Planning in Uncertain Environments. 463-469
  
• Michael Pittarelli:
  Anytime Decision Making with Imprecise Probabilities. 470-477
  
• William B. Poland, Ross D. Shachter:
  Three Approaches to Probability Model Selection. 478-483
  
• Malcolm Pradhan, Gregory M. Provan, Blackford Middleton, Max Henrion:
  Knowledge Engineering for Large Belief Networks. 484-490
  
• Runping Qi, Nevin Lianwen Zhang, David Poole:
  Solving Asymmetric Decision Problems with Influence Diagrams. 491-497
  
• Marco Ramoni, Alberto Riva:
  Belief Maintenance in Bayesian Networks. 498-505
  
• Eugene Santos Jr., Solomon Eyal Shimony:
  Belief Updating by Enumerating High-Probability Independence-based Assignments. 506-513
  
• Ross D. Shachter, Stig K. Andersen, Peter Szolovits:
  Global Conditioning for Probabilistic Inference in Belief Networks. 514-522
  
• Philippe Smets:
  Belief Induced by the Partial Knowledge of the Probabilities. 523-530
  
• Paul Snow:
  Ignorance and the Expressiveness of Single- and Set-Valued Probability Models of Belief. 531-537
  
• Sampath Srinivas:
  A Probabilistic Approach to Hierarchical Model-based Diagnosis. 538-545
  
• Milan Studený:
  Semigraphoids Are Two-Antecedental Approximations of Stochastic Conditional Independence Models. 546-552
  
• Sek-Wah Tan:
  Exceptional Subclasses in Qualitative Probability. 553-559
  
• Pei Wang:
  A Defect in Dempster-Shafer Theory. 560-566
  
• Michael P. Wellman, Chao-Lin Liu:
  State-Space Abstraction for Anytime Evaluation of Probabilistic Networks. 567-574
  
• Emil Weydert:
  General Belief Measures. 575-582
  
• Nic Wilson:
  Generating Graphoids from Generalised Conditional Probability. 583-590
  
• S. K. Michael Wong, Zhiwei Wang:
  On Axiomatization of Probabilistic Conditional Independencies. 591-597
  
• Hong Xu, Philippe Smets:
  Evidential Reasoning with Conditional Belief Functions. 598-605
  
• Nevin Lianwen Zhang, David Poole:
  Intercausal Independence and Heterogeneous Factorization. 606-614