> Nong Ye wrote: > > > I am interested in work and literature on the incremental learning of > > Bayesian networks. > > Here is my short bib-list of papers on that topic; several of them are > also in the references section of Moises Goldszmidt's UAI97 paper he > mentioned earlier. > > Alex Bronstein > HP Labs, Palo Alto, CA I have added a reference at the end of the list; it is an extension of Spiegelhalter and Lauritzen's [1990] work on sequential updating of conditional probabilities. Best regards Javier D�ez ------------------------------------------------------------------------- F. J. Diez Phone: +34-91-3987161 Dpto. Inteligencia Artificial. UNED Fax: +34-91-3986697 Senda del Rey, 9 E-mail: [EMAIL PROTECTED] 28040 Madrid. Spain WWW: http://www.dia.uned.es/~fjdiez 1. Bauer, E., Koller, D., & Singer, Y. (1997). Update rules for parameter estimation in Bayesian networks. In Geiger, Dan and Shenoy, Prakash (eds.), Proceedings of the 13th Annual Conference on Uncertainty in Artificial Intelligence UAI-97, Providence, RI, August 1-3, 1997. (pp. 3-13). San Mateo, CA: Morgan Kaufmann. 2. Boyen, X., & Koller, D. (1999). Approximate learning of dynamic models. In Kearns, M. S., Solla, S. A., and Cohn, D. A. (eds.), Proceedings of Neural Information Processing Systems NIPS-98, Denver, CO, November 1998. Vol. 11 Cambridge, MA: MIT Press. 3. Elkan, Charles. (1997). Boosting and Naive Bayesian Learning. (Report No. CS97-557). San Diego, CA: Dept of CS&E. 4. Friedman, N., & Goldszmidt, M. (1997). Sequential update of Bayesian network structure. In Geiger, Dan and Shenoy, Prakash (eds.), Proceedings of the 13th Annual Conference on Uncertainty in Artificial Intelligence UAI-97, Providence, RI, August 1-3, 1997. San Mateo, CA: Morgan Kaufmann. 5. Heckerman, David. (1995). A Tutorial on Learning With Bayesian Networks. (Report No. MSR-TR-95-06). Redmond, WA: Microsoft Research. 6. Olesen, K. G., Lauritzen, S. L., & Jensen, F. V. (1992). aHUGIN: a system creating adaptive causal probabilistic networks. In Dubois, Didier, Wellman, Michael P., D'Ambrosio, Bruce, and Smets, Phillipe (eds.), Proceedings of the 8th Annual Conference on Uncertainty in Artificial Intelligence UAI-92, Stanford University, CA, July 17-19, 1992. (pp. 223-229). San Mateo, CA: Morgan Kaufmann. 7. Ramachandran, S., & Mooney, R. J. (1998). Theory refinement for Bayesian networks with hidden variables. In Proceedings of the 15th International Conference on Machine Learning ICML-98, Madison, WI, July 24-27, 1998. (pp. 454-462). San Mateo, CA: Morgan Kaufmann. 8. Spiegelhalter, D. J., & Lauritzen, S. L. (1990). Sequential updating of conditional probabilities on directed graphical structures. Networks, 20, 579-605. 9. Diez, F. J. (1993). Parameter adjustement in Bayes networks. The generalized noisy OR-gate. In Heckerman and Mamdani (eds.), Proceedings of the 9th Conference on Uncertainty in Artificial Intelligence UAI-93, Washington D.C., 1993. San Mateo, CA: Morgan Kaufmann.
