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ORCID10th UAI 1994: Seattle, Washington, USA
- Ramón López de Mántaras, David Poole:
UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, Seattle, Washington, USA, July 29-31, 1994. Morgan Kaufmann 1994, ISBN 1-55860-332-8 - 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, Lluís 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 L. 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 L. Poole:
Intercausal Independence and Heterogeneous Factorization. 606-614
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