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Titlebook: Neural Networks: Tricks of the Trade; Grégoire Montavon,Geneviève B. Orr,Klaus-Robert Mü Book 2012Latest edition Springer-Verlag Berlin He

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樓主: FAD
21#
發(fā)表于 2025-3-25 07:00:32 | 只看該作者
Efficient BackPropackprop can be avoided with tricks that are rarely exposed in serious technical publications. This paper gives some of those tricks, and offers explanations of why they work..Many authors have suggested that second-order optimization methods are advantageous for neural net training. It is shown that
22#
發(fā)表于 2025-3-25 07:59:10 | 只看該作者
Early Stopping — But When?o avoid the overfitting (“early stopping”). The exact criterion used for validation-based early stopping, however, is usually chosen in an ad-hoc fashion or training is stopped interactively. This trick describes how to select a stopping criterion in a systematic fashion; it is a trick for either sp
23#
發(fā)表于 2025-3-25 14:04:07 | 只看該作者
24#
發(fā)表于 2025-3-25 18:05:57 | 只看該作者
25#
發(fā)表于 2025-3-25 22:43:33 | 只看該作者
26#
發(fā)表于 2025-3-26 02:57:49 | 只看該作者
Large Ensemble Averaging an infinite ensemble of predictors from finite (small size) ensemble information. We demonstrate it on ensembles of networks with different initial choices of synaptic weights. We find that the optimal stopping criterion for large ensembles occurs later in training time than for single networks. We
27#
發(fā)表于 2025-3-26 05:28:31 | 只看該作者
28#
發(fā)表于 2025-3-26 09:21:42 | 只看該作者
A Dozen Tricks with Multitask Learningning signals of other . tasks. It does this by learning the extra tasks in parallel with the main task while using a shared representation; what is learned for each task can help other tasks be learned better. This chapter describes a dozen opportunities for applying multitask learning in real probl
29#
發(fā)表于 2025-3-26 14:37:25 | 只看該作者
30#
發(fā)表于 2025-3-26 19:01:41 | 只看該作者
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