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10 items by relevance
1 Book chapter

Sequential Monte Carlo Methods for Neural Networks

Freitas, J.F.G. de; Andreiu, C.; Højen-Sørensen, Pedro; Nirandan, M.; Gee, A.H.

Sequential Monte Carlo Methods in Practice — 2001

Year: 2001

Language: English

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2 Journal article

Sequential monte carlo methods To train neural network models

de Freitas JF; M Niranjan M; Gee; doucet

Neural Computation — 2000, Volume 12, Issue 4, pp. 955-93

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

Year: 2000

Language: English

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3 Conference paper

Hybrid sequential Monte Carlo/Kalman methods to train neural networks in non-stationary environments

De Freitas, J.F.; Niranjan, M.; Gee, A.H.

1999 Ieee International Conference on Acoustics, Speech, and Signal Processing. Proceedings. Icassp99 (cat. No.99ch36258) — 1999, Volume 2, pp. 1057,1058,1059,1060

We propose a novel sequential algorithm for training neural networks in non-stationary environments. The approach is based on a Monte Carlo method known as the sampling-importance resampling simulation algorithm. We derive our algorithm using a Bayesian framework, which allows us to learn

Year: 1999

Language: English

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