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Global optimisation of neural network models via sequential sampling-importance resampling.

, , , and . ICSLP, ISCA, (1998)

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Dynamic Learning with the EM Algorithm for Neural Networks., , and . VLSI Signal Processing, 26 (1-2): 119-131 (2000)Hybrid sequential Monte Carlo/Kalman methods to train neural networks in non-stationary environments., , and . ICASSP, page 1057-1060. IEEE Computer Society, (1999)Speech Modelling Using Subspace and EM Techniques., , , and . NIPS, page 796-802. The MIT Press, (1999)Global Optimisation of Neural Network Models via Sequential Sampling., , , and . NIPS, page 410-416. The MIT Press, (1998)Sequential Monte Carlo Methods to Train Neural Network Models., , , and . Neural Computation, 12 (4): 955-993 (2000)Robust Full Bayesian Methods for Neural Networks., , and . NIPS, page 379-385. The MIT Press, (1999)Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary., , , and . ECCV (4), volume 2353 of Lecture Notes in Computer Science, page 97-112. Springer, (2002)Global optimisation of neural network models via sequential sampling-importance resampling., , , and . ICSLP, ISCA, (1998)Hierarchical Bayesian Models for Regularization in Sequential Learning., , and . Neural Computation, 12 (4): 933-953 (2000)Regularisation in Sequential Learning Algorithms., , and . NIPS, page 458-464. The MIT Press, (1997)