701. K. Crammer and Y. Singer (2002) On the learnability and design of output codes for multiclass problems, Machine Learning 47(2): 201–33.
702. M.F. Balcan, A. Blum, and K. Yang (2005) Co-training and expansion: Towards bridging theory and practice, Advances in Neural Information Processing Systems, 17: 89–96.
703. Wikipedia, Semi-supervised learning–Wikipedia, The Free Encyclopedia. http://en.wikipedia.org/wiki/Semi supervised learning.
704. O. Chapelle, B. Schölkopf, and A. Zien (2006) Semi-supervised Learning, vol. 2. Cambridge, MA: MIT Press.
705. N. Adams (2009) Semi-supervised learning, Journal of the Royal Statistical Society: Series A (Statistics in Society) 172(2): 530.
706. N. Grira, M. Crucianu, and N. Boujemaa (2004) Unsupervised and Semi-supervised Clustering: A Brief Survey: A Review of Machine Learning Techniques for Processing Multimedia Content, Report of the MUSCLE European Network of Excellence (FP6).
707. S. Basu, I. Davidson, and K.L. Wagstaff (2008) Constrained Clustering: Advances in Algorithms, Theory, and Applications. Chapman & Hall/CRC.
708. E.P. Xing, A.Y. Ng, M.I. Jordan, and S. Russell (2002) Distance metric learning, with application to clustering with side-information, Advances in Neural Information Processing Systems 15: 505–12.
709. S. Basu, A. Banerjee, and R. Mooney (2002) Semi-supervised clustering by seeding, in Proceedings of 19th International Conference on Machine Learning, pp. 19–26.
710. A. Blum and T. Mitchell (1998) Combining labeled ...
Get Cognitive Radio Communication and Networking: Principles and Practice 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.
