11. UAI 1995: Montreal, Quebec, Canada
Philippe Besnard, Steve Hanks (Eds.): 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- Salem Benferhat, Alessandro Saffiotti, Philippe Smets: Belief functions and default reasoning. 19-26
- 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
- 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
- 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
- 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
- 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
- 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, 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, 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
- Keiji Kanazawa, Daphne Koller, Stuart J. 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
- Nevin Lianwen Zhang: Inference with Causal Independence in the CPSC Network. 582-589
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