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ORCID11th UAI 1995: Montreal, Quebec, Canada
- Philippe Besnard, Steve Hanks:
UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, Montreal, Quebec, Canada, August 18-20, 1995. Morgan Kaufmann 1995, ISBN 1-55860-385-9 - Fahiem Bacchus, Adam J. Grove:
Graphical models for preference and utility. 3-10 - Alexander Balke, Judea Pearl:
Counterfactuals and Policy Analysis in Structural Models. 11-18 - Salem Benferhat, Alessandro Saffiotti, Philippe Smets:
Belief functions and default reasoning. 19-26 - Luca Boldrin, Claudio Sossai:
An Algebraic Semantics for Possibilistic Logic. 27-35 - John S. Breese, Russ Blake:
Automating Computer Bottleneck Detection with Belief Nets. 36-45 - Wray L. Buntine:
Chain graphs for learning. 46-54 - Enrique F. Castillo, Remco R. Bouckaert, José María Sarabia, Cristina Solares:
Error Estimation in Approximate Bayesian Belief Network Inference. 55-62 - Juan Luis Castro, Jose Manuel Zurita:
Generating the Structure of a Fuzzy Rule under Uncertainty. 63-67 - Didier Cayrac, Didier Dubois, Henri Prade:
Practical model-based diagnosis with qualitative possibilistic uncertainty. 68-76 - Tom Chávez, Ross D. Shachter:
Decision Flexibility. 77-86 - David Maxwell Chickering:
A Transformational Characterization of Equivalent Bayesian Network Structures. 87-98 - Adnan Darwiche:
Conditioning Algorithms for Exact and Approximate Inference in Causal Networks. 99-107 - Luis M. de Campos, Serafín Moral:
Independence Concepts for Convex Sets of Probabilities. 108-115 - Arthur L. Delcher, Adam J. Grove, Simon Kasif, Judea Pearl:
Logarithmic-Time Updates and Queries in Probabilistic Networks. 116-124 - Denise Draper:
Clustering Without (Thinking About) Triangulation. 125-133 - Eric Driver, Darryl Morrell:
Implementation of Continuous Bayesian Networks Using Sums of Weighted Gaussians. 134-140 - Marek J. Druzdzel, Linda C. van der Gaag:
Elicitation of Probabilities for Belief Networks: Combining Qualitative and Quantitative Information. 141-148 - Didier Dubois, Henri Prade:
Numerical representations of acceptance. 149-156 - Kazuo J. Ezawa, Til Schuermann:
Fraud/Uncollectible Debt Detection Using a Bayesian Network Based Learning System: A Rare Binary Outcome with Mixed Data Structures. 157-166 - Hélène Fargier, Jérôme Lang, Roger Martin-Clouaire, Thomas Schiex:
A constraint satisfaction framework for decision under uncertainty. 167-174 - Nir Friedman, Joseph Y. Halpern:
Plausibility Measures: A User's Guide. 175-184 - David Galles, Judea Pearl:
Testing Identifiability of Causal Effects. 185-195 - Dan Geiger, David Heckerman:
A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks. 196-207 - Moisés Goldszmidt:
Fast Belief Update Using Order-of-Magnitude Probabilities. 208-216 - Benjamin N. Grosof:
Transforming Prioritized Defaults and Specificity into Parallel Defaults. 217-228 - Peter Haddawy, AnHai Doan, Richard Goodwin:
Efficient Decision-Theoretic Planning: Techniques and Empirical Analysis. 229-236 - Petr Hájek, Lluís Godo, Francesc Esteva:
Fuzzy logic and probability. 237-244 - Steve Hanks, David Madigan, Jonathan Gavrin:
Probabilistic Temporal Reasoning with Endogenous Change. 245-254 - David Harmanec:
Toward a Characterization of Uncertainty Measure for the Dempster-Shafer Theory. 255-261 - David Heckerman, Ross D. Shachter:
A Definition and Graphical Representation for Causality. 262-273 - David Heckerman, Dan Geiger:
Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains. 274-284 - David Heckerman:
A Bayesian Approach to Learning Causal Networks. 285-295 - Eric Horvitz, Matthew Barry:
Display of Information for Time-Critical Decision Making. 296-305 - Eric Horvitz, Adrian C. Klein:
Reasoning, Metareasoning, and Mathematical Truth: Studies of Theorem Proving under Limited Resources. 306-314 - Mark Hulme:
Improved Sampling for Diagnostic Reasoning in Bayesian Networks. 315-322 - Finn Verner Jensen:
Cautious Propagation in Bayesian Networks. 323-328 - Ali Jenzarli:
Information/Relevance Influence Diagrams. 329-337 - George H. John, Pat Langley:
Estimating Continuous Distributions in Bayesian Classifiers. 338-345 - Keiji Kanazawa, Daphne Koller, Stuart Russell:
Stochastic simulation algorithms for dynamic probabilistic networks. 346-351 - Grigoris I. Karakoulas:
Probabilistic Exploration in Planning while Learning. 352-361 - Young-Gyun Kim, Marco Valtorta:
On the Detection of Conflicts in Diagnostic Bayesian Networks Using Abstraction. 362-367 - Uffe Kjærulff:
HUGS: Combining Exact Inference and Gibbs Sampling in junction Trees. 368-375 - Alexander V. Kozlov, Jaswinder Pal Singh:
Sensitivities: An Alternative to Conditional Probabilities for Bayesian Belief Networks. 376-385 - Paul J. Krause, John Fox, Philip N. Judson:
Is There a Role for Qualitative Risk Assessment? 386-393 - Michael L. Littman, Thomas L. Dean, Leslie Pack Kaelbling:
On the Complexity of Solving Markov Decision Problems. 394-402 - Christopher Meek:
Causal inference and causal explanation with background knowledge. 403-410 - Christopher Meek:
Strong completeness and faithfulness in Bayesian networks. 411-418 - Liem Ngo, Peter Haddawy, James Helwig:
A Theoretical Framework for Context-Sensitive Temporal Probability Model Construction with Application to Plan Projection. 419-426 - Simon Parsons:
Refining reasoning in qualitative probabilistic networks. 427-434 - Judea Pearl:
On the Testability of Causal Models With Latent and Instrumental Variables. 435-443 - Judea Pearl, James M. Robins:
Probabilistic evaluation of sequential plans from causal models with hidden variables. 444-453 - David Poole:
Exploiting the Rule Structure for Decision Making within the Independent Choice Logic. 454-463 - Gregory M. Provan:
Abstraction in Belief Networks: The Role of Intermediate States in Diagnostic Reasoning. 464-471 - David V. Pynadath, Michael P. Wellman:
Accounting for Context in Plan Recognition, with Application to Traffic Monitoring. 472-481 - Prakash P. Shenoy:
A New Pruning Method for Solving Decision Trees and Game Trees. 482-490 - Peter Spirtes:
Directed Cyclic Graphical Representations of Feedback Models. 491-498 - Peter Spirtes, Christopher Meek, Thomas S. Richardson:
Causal Inference in the Presence of Latent Variables and Selection Bias. 499-506 - Sampath Srinivas:
Modeling failure priors and persistence in model-based diagnosis. 507-514 - Sampath Srinivas:
A polynomial algorithm for computing the optimal repair strategy in a system with independent component failures. 515-522 - Sampath Srinivas, Eric Horvitz:
Exploiting System Hierarchy to Compute Repair Plans in Probabilistic Model-Based Diagnosis. 523-531 - Michael P. Wellman, Matthew Ford, Kenneth Larson:
Path Planning under Time-Dependent Uncertainty. 532-539 - Emil Weydert:
Defaults and Infinitesimals Defeasible Inference by Nonarchimedean Entropy-Maximization. 540-547 - Nic Wilson:
An Order of Magnitude Calculus. 548-555 - S. K. Michael Wong, Cory J. Butz, Yang Xiang:
A Method for Implementing a Probabilistic Model as a Relational Database. 556-564 - Yang Xiang:
Optimization of Inter-Subnet Belief Updating in Multiply Sectioned Bayesian Networks. 565-573 - Hong Xu, Philippe Smets:
Generating Explanations for Evidential Reasoning. 574-581 - Nevin Lianwen Zhang:
Inference with Causal Independence in the CPSC Network. 582-589
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