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Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective?

, , , , and . NIPS, page 176-182. MIT Press, (1995)

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The Efficiency and the Robustness of Natural Gradient Descent Learning Rule., and . NIPS, page 385-391. The MIT Press, (1997)Blind system identification using multiple sensors., , and . ICASSP, page 3171-3174. IEEE Computer Society, (1995)Complexity Issues in Natural Gradient Descent Method for Training Multi-Layer Perceptrons., and . Neural Computation, 10 (8): 2137-2157 (1998)Information backpropagation for blind separation of sources in nonlinear mixture., , and . ICNN, page 2141-2146. IEEE, (1997)Information-theoretic approach to blind separation of sources in non-linear mixture., , and . Signal Processing, 64 (3): 291-300 (1998)Two Gradient Descent Algorithms for Blind Signal Separation., and . ICANN, volume 1112 of Lecture Notes in Computer Science, page 287-292. Springer, (1996)Performance comparison of two methods for 2-D frequency estimation in both medium and high SNR cases., and . Signal Processing, 58 (2): 215-221 (1997)Search for Information Bearing Components in Speech., and . NIPS, page 803-812. The MIT Press, (1999)Relevancy of time-frequency features for phonetic classification measured by mutual information., , and . ICASSP, page 225-228. IEEE Computer Society, (1999)Asymptotic statistical theory of overtraining and cross-validation., , , , and . IEEE Trans. Neural Networks, 8 (5): 985-996 (1997)