Abstract is missing.
- On the Semantics and Automated Deduction for PLFC, a Logic of Possibilistic Uncertainty and FuzzinessTeresa Alsinet, Lluis Godo, Sandra Sandri. 3-12 [doi]
- A Temporal Bayesian Network for Diagnosis and PredictionGustavo Arroyo-Figueroa, Luis Enrique Sucar. 13-20 [doi]
- Inferring Parameters and Structure of Latent Variable Models by Variational BayesHagai Attias. 21-30 [doi]
- Relative Loss Bounds for On-line Density Estirnation with the Exponential Family of DistributionsKaty S. Azoury, Manfred K. Warmuth. 31-40 [doi]
- An Application of Uncertain Reasoning to Requirements EngineeringPhilip S. Barry, Kathryn B. Laskey. 41-48 [doi]
- Random Algorithms for the Loop Cutset ProblemAnn Becker, Reuven Bar-Yehuda, Dan Geiger. 49-56 [doi]
- Possibilistic logic bases and possibilistic graphsSalem Benferhat, Didier Dubois, Laurent Garcia, Henri Prade. 57-64 [doi]
- Artificial Decision Making Under Uncertainty in Intelligent BuildingsMagnus Boman, Paul Davidsson, Håkan L. S. Younes. 65-70 [doi]
- Reasoning With Conditional Ceteris Paribus Preference StatementsCraig Boutilier, Ronen I. Brafman, Holger H. Hoos, David Poole. 71-80 [doi]
- Continuous Value Function Approximation for Sequential Bidding PoliciesCraig Boutilier, Moisés Goldszmidt, Bikash Sabata. 81-90 [doi]
- Discovering the Hidden Structure of Complex Dynamic SystemsXavier Boyen, Nir Friedman, Daphne Koller. 91-100 [doi]
- Comparing Bayesian Network ClassifiersJie Cheng, Russell Greiner. 101-108 [doi]
- Fast Learning from Sparse DataDavid Maxwell Chickering, David Heckerman. 109-115 [doi]
- Causal Discovery from a Mixture of Experimental and Observational DataGregory F. Cooper, Changwon Yoo. 116-125 [doi]
- Loglinear models for first-order probabilistic reasoningJames Cussens. 126-133 [doi]
- Learning PolytreesSanjoy Dasgupta. 134-141 [doi]
- A Hybrid Anytime Algorithm for the Construction of Causal Models From Sparse DataDenver Dash, Marek J. Druzdzel. 142-149 [doi]
- Model based Bayesian ExplorationRichard Dearden, Nir Friedman, David Andre. 150-159 [doi]
- Hybrid Probabilistic Programs: Algorithms and ComplexityMichael I. Dekhtyar, Alex Dekhtyar, V. S. Subrahmanian. 160-169 [doi]
- Assessing the value of a candidate: Comparing belief function and possibility theoriesDidier Dubois, Michel Grabisch, Henri Prade, Philippe Smets. 170-177 [doi]
- Evaluation of Distributed Intelligence on the Smart CardKazuo J. Ezawa, Gregory Napiorkowski, Mariusz Kossarski. 178-187 [doi]
- Qualitative Models for Decision Under Uncertainty without the Commensurability AssumptionHélène Fargier, Patrice Perny. 188-195 [doi]
- Data Analysis with Bayesian Networks: A Bootstrap ApproachNir Friedman, Moisés Goldszmidt, Abraham Wyner. 196-205 [doi]
- Learning Bayesian Network Structure from Massive Datasets: The Sparse Candidate AlgorithmNir Friedman, Iftach Nachman, Dana Pe er. 206-215 [doi]
- Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability DistributionsDan Geiger, James Cussens. 216-225 [doi]
- Quantifier Elimination for Statistical ProblemsDan Geiger, Christopher Meek. 226-235 [doi]
- On Transformations between Probability and Spolinian Disbelief FunctionsPhan Hong Giang, Prakash P. Shenoy. 236-244 [doi]
- A New Model of Plan RecognitionRobert P. Goldman, Christopher W. Geib, Christopher A. Miller. 245-254 [doi]
- Multi-objects association in perception of dynamical situationDominique Gruyer, Véronique Berge-Cherfaoui. 255-262 [doi]
- A Hybrid Approach to Reasoning with Partially Elicited Preference ModelsVu A. Ha, Peter Haddawy. 263-270 [doi]
- Faithful Approximations of Belief FunctionsDavid Harmanec. 271-278 [doi]
- SPUDD: Stochastic Planning using Decision DiagramsJesse Hoey, Robert St-Aubin, Alan J. Hu, Craig Boutilier. 279-288 [doi]
- Probabilistic Latent Semantic AnalysisThomas Hofmann. 289-296 [doi]
- Estimating the Value of Computation in Flexible Information RefinementMichael C. Horsch, David Poole. 297-304 [doi]
- Attention-Sensitive AlertingEric Horvitz, Andy Jacobs, David Hovel. 305-313 [doi]
- Mini-Bucket Heuristics for Improved SearchKalev Kask, Rina Dechter. 314-323 [doi]
- A General Algorithm for Approximate Inference and Its Application to Hybrid Bayes NetsDaphne Koller, Uri Lerner, Dragomir Anguelov. 324-333 [doi]
- On Supervised Selection of Bayesian NetworksPetri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri. 334-342 [doi]
- Bayesian PokerKevin B. Korb, Ann E. Nicholson, Nathalie Jitnah. 343-350 [doi]
- On Quantified Linguistic ApproximationRyszard Kowalczyk. 351-358 [doi]
- Choosing Among Interpretations of ProbabilityHenry E. Kyburg Jr., Choh-Man Teng. 359-365 [doi]
- Expected Utility NetworksPierfrancesco La Mura, Yoav Shoham. 366-373 [doi]
- My Brain is Full: When More Memory HelpsChristopher Lusena, Tong Li, Shelia Sittinger, Chris Wells, Judy Goldsmith. 374-381 [doi]
- Lazy Evaluation of Symmetric Bayesian Decision ProblemsAnders L. Madsen, Finn Verner Jensen. 382-390 [doi]
- Representing and Combining Partially Specified CPTsSuzanne M. Mahoney, Kathryn B. Laskey. 391-400 [doi]
- On the Complexity of Policy IterationYishay Mansour, Satinder P. Singh. 401-408 [doi]
- Approximate Planning for Factored POMDPs using Belief State SimplificationDavid A. McAllester, Satinder P. Singh. 409-416 [doi]
- Solving POMDPs by Searching the Space of Finite PoliciesNicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling, Anthony R. Cassandra. 417-426 [doi]
- Learning Finite-State Controllers for Partially Observable EnvironmentsNicolas Meuleau, Leonid Peshkin, Kee-Eung Kim, Leslie Pack Kaelbling. 427-436 [doi]
- Bayes Nets in Educational Assessment: Where the Numbers Come FromRobert Mislevy, Russell Almond, Duanli Yan, Linda S. Steinberg. 437-446 [doi]
- A Bayesian Network Classifier that Combines a Finite Mixture Model and a NaIve Bayes ModelStefano Monti, Gregory F. Cooper. 447-456 [doi]
- A Variational Approximation for Bayesian Networks with Discrete and Continuous Latent VariablesKevin P. Murphy. 457-466 [doi]
- Loopy Belief Propagation for Approximate Inference: An Empirical StudyKevin P. Murphy, Yair Weiss, Michael I. Jordan. 467-475 [doi]
- Learning Bayesian Networks from Incomplete Data with Stochastic Search AlgorithmsJames W. Myers, Kathryn B. Laskey, Tod S. Levitt. 476-485 [doi]
- Learning Bayesian Networks with Restricted Causal InteractionsJulian R. Neil, Chris S. Wallace, Kevin B. Korb. 486-493 [doi]
- The Decision-Theoretic Interactive Video AdvisorHien Nguyen, Peter Haddawy. 494-501 [doi]
- Welldefined Decision ScenariosThomas D. Nielsen, Finn Verner Jensen. 502-511 [doi]
- Accelerating EM: An Empirical StudyLuis E. Ortiz, Leslie Pack Kaelbling. 512-521 [doi]
- Variational Learning in Mixed-State Dynamic Graphical ModelsVladimir Pavlovic, Brendan J. Frey, Thomas S. Huang. 522-530 [doi]
- Graphical Representations of Consensus BeliefDavid M. Pennock, Michael P. Wellman. 531-540 [doi]
- SPOOK: A system for probabilistic object-oriented knowledge representationAvi Pfeffer, Daphne Koller, Brian Milch, Ken T. Takusagawa. 541-550 [doi]
- Bayesian Networks for Dependability Analysis: an Application to Digital Control ReliabilityLuigi Portinale, Andrea Bobbio. 551-558 [doi]
- Enhancing QPNs for Trade-off ResolutionSilja Renooij, Linda C. van der Gaag. 559-566 [doi]
- A Possibilistic Model for Qualitative Sequential Decision Problems under Uncertainty in Partially Observable EnvironmentsRégis Sabbadin. 567-574 [doi]
- Inference Networks and the Evaluation of Evidence: Alternative AnalysesDavid A. Schum. 575-584 [doi]
- Approximate Learning in Complex Dynamic Bayesian NetworksRaffaella Settimi, Jim Q. Smith, A. S. Gargoum. 585-593 [doi]
- Efficient Value of Information ComputationRoss D. Shachter. 594-601 [doi]
- Learning Hidden Markov Models with Geometrical ConstraintsHagit Shatkay. 602-611 [doi]
- Practical Uses of Belief FunctionsPhilippe Smets. 612-621 [doi]
- Multiplicative Factorization of Noisy-MaxMasami Takikawa, Bruce D Ambrosio. 622-630 [doi]
- An Update Semantics for Defeasible ObligationsLeendert W. N. van der Torre, Yao-Hua Tan. 631-638 [doi]
- Mixture Approximations to Bayesian NetworksVolker Tresp, Michael Haft, Reimar Hofmann. 639-646 [doi]
- How to Elicit Many ProbabilitiesLinda C. van der Gaag, Silja Renooij, C. L. M. Witteman, B. M. P. Aleman, B. G. Taal. 647-654 [doi]
- Probabilistic Belief Change: Expansion, Conditioning and ConstrainingFrans Voorbraak. 655-662 [doi]
- Bayesian Control for Concentrating Mixed Nuclear WasteRobert L. Welch, Clayton Smith. 663-669 [doi]
- Contextual Weak Independence in Bayesian NetworksS. K. Michael Wong, Cory J. Butz. 670-679 [doi]
- Inference in Multiply Sectioned Bayesian Networks with Extended Shafer-Shenoy and Lazy PropagationYanping Xiang, Finn Verner Jensen. 680-687 [doi]
- Time-Critical Dynamic Decision MakingYanping Xiang, Kim-Leng Poh. 688-695 [doi]
- A Method for Speeding Up Value Iteration in Partially Observable Markov Decision ProcessesNevin Lianwen Zhang, Stephen S. Lee, Weihong Zhang. 696-703 [doi]