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ORCID12th UAI 1996: Portland, Oregon, USA
- Eric Horvitz, Finn Verner Jensen:
UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, Reed College, Portland, Oregon, USA, August 1-4, 1996. Morgan Kaufmann 1996, ISBN 1-55860-412-X - Silvia Acid, Luis M. de Campos:
An Algorithm for Finding Minimum d-Separating Sets in Belief Networks. 3-10 - John Mark Agosta:
Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response. 11-19 - Satnam Alag, Alice M. Agogino:
Inference Using Message Propagation and Topology Transformation in Vector Gaussian Continuous Networks. 20-27 - Constantin F. Aliferis, Gregory F. Cooper:
A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling Techniques. 28-39 - Steen A. Andersson, David Madigan, Michael D. Perlman:
An Alternative Markov Property for Chain Graphs. 40-48 - Ella M. Atkins, Edmund H. Durfee, Kang G. Shin:
Plan Development using Local Probabilistic Models. 49-56 - Donald Bamber:
Entailment in Probability of Thresholded Generalizations. 57-64 - Claude Barrouil, Jerome Lemaire:
Object Recognition with Imperfect Perception and Redundant Description. 65-72 - Mathias Bauer:
Approximations for Decision Making in the Dempster-Shafer Theory of Evidence. 73-80 - Ann Becker, Dan Geiger:
A sufficiently fast algorithm for finding close to optimal junction trees. 81-89 - Salem Benferhat, Didier Dubois, Henri Prade:
Coping with the Limitations of Rational Inference in the Framework of Possibility Theory. 90-97 - Blai Bonet, Hector Geffner:
Arguing for Decisions: A Qualitative Model of Decision Making. 98-105 - Craig Boutilier:
Learning Conventions in Multiagent Stochastic Domains using Likelihood Estimates. 106-114 - Craig Boutilier, Nir Friedman, Moisés Goldszmidt, Daphne Koller:
Context-Specific Independence in Bayesian Networks. 115-123 - John S. Breese, David Heckerman:
Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment. 124-132 - Enrique F. Castillo, Cristina Solares, Patricia Gómez:
Tail Sensitivity Analysis in Bayesian Networks. 133-140 - Tom Chávez:
Decision-Analytic Approaches to Operational Decision Making: Application and Observation. 141-149 - David Maxwell Chickering:
Learning Equivalence Classes of Bayesian Network Structures. 150-157 - David Maxwell Chickering, David Heckerman:
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network. 158-168 - Lonnie Chrisman:
Independence with Lower and Upper Probabilities. 169-177 - Lonnie Chrisman:
Propagation of 2-Monotone Lower Probabilities on an Undirected Graph. 178-185 - Fábio Gagliardi Cozman, Eric Krotkov:
Quasi-Bayesian Strategies for Efficient Plan Generation: Application to the Planning to Observe Problem. 186-193 - Bruce D'Ambrosio, Scott Burgess:
Some Experiments with Real-time Decision Algorithms. 194-202 - Adnan Darwiche, Gregory M. Provan:
Query DAGs: A practical paradigm for implementing belief-network inference. 203-210 - Rina Dechter:
Bucket elimination: A unifying framework for probabilistic inference. 211-219 - Rina Dechter:
Topological parameters for time-space tradeoff. 220-227 - AnHai Doan, Peter Haddawy:
Sound Abstraction of Probabilistic Actions in The Constraint Mass Assignment Framework. 228-235 - Didier Dubois, Henri Prade:
Belief Revision with Uncertain Inputs in the Possibilistic Setting. 236-243 - Yousri El Fattah, Rina Dechter:
An evaluation of structural parameters for probabilistic reasoning: Results on benchmark circuits. 244-251 - Nir Friedman, Moisés Goldszmidt:
Learning Bayesian Networks with Local Structure. 252-262 - Nir Friedman, Joseph Y. Halpern:
A Qualitative Markov Assumption and Its Implications for Belief Change. 263-273 - Nir Friedman, Zohar Yakhini:
On the Sample Complexity of Learning Bayesian Networks. 274-282 - Dan Geiger, David Heckerman, Christopher Meek:
Asymptotic Model Selection for Directed Networks with Hidden Variables. 283-290 - Vu A. Ha, Peter Haddawy:
Theoretical Foundations for Abstraction-Based Probabilistic Planning. 291-298 - Joseph Y. Halpern:
Defining Relative Likelihood in Partially-Ordered Preferential Structures. 299-306 - Max Henrion, Malcolm Pradhan, Brendan Del Favero, Kurt Huang, Gregory M. Provan, Paul O'Rorke:
Why is diagnosis using belief networks insensitive to imprecision in probabilities? 307-314 - Michael C. Horsch, David L. Poole:
Flexible Policy Construction by Information Refinement. 315-324 - Kurt Huang, Max Henrion:
Efficient Search-Based Inference for noisy-OR Belief Networks: TopEpsilon. 325-331 - Pablo H. Ibargüengoytia, Luis Enrique Sucar, Sunil Vadera:
A Probabilistic Model for Sensor Validation. 332-339 - Tommi S. Jaakkola, Michael I. Jordan:
Computing upper and lower bounds on likelihoods in intractable networks. 340-348 - Allan Leck Jensen, Finn Verner Jensen:
MIDAS: An Influence Diagram for Management of Mildew in Winter Wheat. 349-356 - Alexander V. Kozlov, Jaswinder Pal Singh:
Computational complexity reduction for BN2O networks using similarity of states. 357-364 - Henry E. Kyburg Jr.:
Uncertain Inferences and Uncertain Conclusions. 365-372 - Kathryn B. Laskey, Laura Martignon:
Bayesian Learning of Loglinear Models for Neural Connectivity. 373-380 - Daniel Lehmann:
Generalized Qualitative Probability: Savage revisited. 381-388 - Suzanne M. Mahoney, Kathryn B. Laskey:
Network Engineering for Complex Belief Networks. 389-396 - Liem Ngo:
Probabilistic Disjunctive Logic Programming. 397-404 - David M. Pennock, Michael P. Wellman:
Toward a Market Model for Bayesian Inference. 405-413 - Mark A. Peot:
Geometric Implications of the Naive Bayes Assumption. 414-419 - Judea Pearl, Rina Dechter:
Identifying Independencies in Causal Graphs with Feedback. 420-426 - Kim-Leng Poh, Eric Horvitz:
A Graph-Theoretic Analysis of Information Value. 427-435 - David Poole:
A Framework for Decision-Theoretic Planning I: Combining the Situation Calculus, Conditional Plans, Probability and Utility. 436-445 - Malcolm Pradhan, Paul Dagum:
Optimal Monte Carlo Estimation of Belief Network Inference. 446-453 - Thomas Richardson:
A Discovery Algorithm for Directed Cyclic Graphs. 454-461 - Thomas Richardson:
A Polynomial-Time Algorithm for Deciding Equivalence of Directed Cyclic Graphical Models. 462-469 - Wilhelm Rödder, Carl-Heinz Meyer:
Coherent Knowledge Processing at Maximum Entropy by SPIRIT. 470-476 - Eugene Santos Jr., Solomon Eyal Shimony, Edward Michael Williams:
Sample-and-Accumulate Algorithms for Belief Updating in Bayes Networks. 477-484 - Ross D. Shachter, Marvin Mandelbaum:
A Measure of Decision Flexibility. 485-491 - Prakash P. Shenoy:
Binary Join Trees. 492-499 - Sampath Srinivas, P. Pandurang Nayak:
Efficient enumeration of instantiations in Bayesian networks. 500-508 - Milan Studený:
On Separation Criterion and Recovery Algorithm for Chain Graphs. 509-516 - Choh Man Teng:
Possible World Partition Sequences: A Unifying Framework for Uncertain Reasoning. 517-524 - Sylvie Thiébaux, Marie-Odile Cordier, Olivier Jehl, Jean-Paul Krivine:
Supply Restoration in Power Distribution Systems: A Case Study in Integrating Model-Based Diagnosis and Repair Planning. 525-532 - Robert L. Welch:
Real Time Estimation of Bayesian Networks. 533-544 - S. K. Michael Wong:
Testing Implication of Probabilistic Dependencies. 545-553 - Peter R. Wurman, Michael P. Wellman:
Optimal Factory Scheduling using Stochastic Dominance A*. 554-563 - Yang Xiang, S. K. Michael Wong, Nick Cercone:
Critical Remarks on Single Link Search in Learning Belief Networks. 564-571
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