5.8. References
[] Aha, D.W., Kibler, D. and Albert, M.K. (1991) Instance-based learning algorithms, Machine Learning, 6, 37.
[] Baluja, S. and Caruana, R. (1995) Removing the genetics from the standard genetic algorithm. Proceedings of the 12th Annual Conference on Machine Learning, p. 38–46, San Francisco.
[] Blake, C.L. and Merz, C.J. (1998) UCI repository of machine learning databases, http://www.ics.uci.edu/∼mlearn/MLRepository.html.
[] Blum, A. and Mitchell, T. (1998) Combining labeled and unlabeled data with co-training. Proceedings of the 11th Annual Conference on Computing Learning Theory, pp. 92–100, New York.
[] Boyan J. and Moore, A. (2000) Learning evaluation functions to improve optimization by local search. Journal of Machine Learning Research, 1, 77–112.
[] Boyan, J.A. and Littman, M.L. (1994) Packet routing in dynamically changing networks: a reinforcement learning approach. In J.D. Cowan, G. Tesauro and J. Alspector (eds.), Advances in Neural Information Processing Systems, volume 6, pp. 671–8, Morgan Kaufmann.
[] Buntine, W. (1996) A guide to the literature on learning probabilistic networks from data. IEEE Transactions on Knowledge and Data Engineering, 8, 195–210.
[] Cheeseman, P., Self, M., Kelly, J., Taylor, W., Freeman, D. and Stutz, J. (1988) Bayesian classification, Proceedings of the Seventh National Conference on Artificial Intelligence, pp. 607–11, St.Paul, MN.
[] Clark, D. (2002) A new vision for network architecture, http://www.isi.edu/∼braden/know-plane/DOCS/DDC_knowledgePlane_3.ps ...
Get Cognitive Networks: Towards Self-Aware Networks now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
