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Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) Book reviews

, , and . IEEE Transactions on Neural Networks, 20 (3): 542-542 (March 2009)
DOI: 10.1109/TNN.2009.2015974

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A Review of Kernel Methods in Machine Learning, , and . Research Report, 156. Max Planck Institute for Technical Cybernetics (MPI), Max Planck Institute for Technical Cybernetics (MPI), (December 2006)Incorporating Invariances in Support Vector Learning Machines, , and . Artificial Neural Networks --- ICANN'96, page 47~-~52. Berlin, Springer Lecture Notes in Computer Science, Vol.~1112, (1996)Shrinking the tube: a new support vector regression algorithm, , , and . Advances in Neural Information Processing Systems 11, page 330 -- 336. Cambridge, MA, MIT Press, (1999)Kernel Principal Component Analysis, , and . Advances in Kernel Methods---Support Vector Learning, page 327--352. (1999)A Generalized Representer Theorem, , and . Proceedings of the Annual Conference on Learning Theory, (2001)Correcting Sample Selection Bias by Unlabeled Data, , , , and . Advances in Neural Information Processing Systems, 19, The MIT Press, Cambridge, MA, (2007)Pre-proceedings version.An Introduction to Kernel-Based learning Algorithms, , , , and . IEEE Transactions on Neural Networks, 12 (2): 181--202 (2001)Semi--supervised Learning, , and . MIT Press, (2006)Extracting support data for a given task, , and . Proceedings of the International Conference on Knowledge Discovery and Data Mining, (1995)Efficient approximations for support vector machines in object detection, , , and . Proc. DAGM�04, (2005)