Gregory F. Cooper

Bibliography

Aliferis, Constantin F. and Cooper, Gregory F. 1994. “An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets.” in UAI-94. Proceedings of the 10th Conference on Uncertainty in Artificial Intelligence, edited by Ramon Lopez de Mantaras and David L. Poole, pp. 8–14. San Francisco, California: Morgan Kaufmann Publishers.
Chavez, R. Martin and Cooper, Gregory F. 1990. “An Empirical Evaluation of a Randomized Algorithm for Probabilistic Inference.” in UAI-89. Proceedings of the 5th Conference on Uncertainty in Artificial Intelligence, volume 5, edited by Max Henrion, Ross D. Shachter, Laveen N. Kanal, and J. F. Lemmer, pp. 60–70. Amsterdam: Elsevier Science Publishers B.V.
Cooper, Gregory F. 1990. “The Computational Complexity of Probabilistic Inference using Bayesian Belief Networks.” Artificial Intelligence 42(3): 393–405.
Cooper, Gregory F. 1992. “A Bayesian Method for Learning Belief Networks that Contain Hidden Variables.”
Cooper, Gregory F. and Herskovits, E. H. 1992. “A Bayesian Method for the Induction of Probabilistic Networks from Data.” Machine Learning 9: 309–347.
Glymour, Clark N. and Cooper, Gregory F., eds. 1999. Computation, Causation and Discovery. Cambridge, Massachusetts: The MIT Press.
Horvitz, Eric J., Cooper, Gregory F. and Heckerman, David E. 1988. “Reflection and Action under Scarce Resources: Theoretical Principles and Empirical Study.” ksl–89–1. Stanford, California: Knowledge Systems Laboratory, Stanford University.
Monti, Stefano and Cooper, Gregory F. 1995. “Bounded Recursive Decomposition: A Search-Based Method for Belief Network Inference Under Limited Resources.” Unpublished manuscript, Intelligent Systems Program, University of Pittsburgh.
Suermondt, H. Jacques and Cooper, Gregory F. 1991. “Initialization for the Method of Conditioning in Bayesian Belief Networks.” Artificial Intelligence 50(1): 83–94.