Sequential Monte Carlo Methods to Train Neural Network Models

Sequential Monte Carlo Methods to Train Neural Network Models

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We discuss a novel strategy for training neural networks using sequential Monte Carlo algorithms and propose a new hybrid gradient descent / sampling importance resampling algorithm (HySIR). In terms of computational time and accuracy, the hybrid SIR is a clear improvement over conventional sequenti...

書誌詳細
主要な著者:	Freitas, D, Nando, Niranjan, M, Gee, A, Doucet, A
フォーマット:	Journal article
出版事項:	2000

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