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J-GLOBAL ID：201902270445774860
Reference number：19A0418940
Learning restricted Boltzmann machine via the adaptive Thouless-Anderson-Palmer mean-field approximation
適応Thouless-Anderson-Palmer近似による勾配法を用いた制限ボルツマンマシンの学習
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Author (3)：
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Material：
Volume：
118
Issue：
284(IBISML2018 44-104)(Web)
Page：
105-110 (WEB ONLY)
Publication year：
Oct. 29, 2018
JST Material Number：
S0532B
ISSN：
0913-5685
Document type：
Proceedings
Article type：
原著論文
Country of issue：
Japan (JPN)
Language：
JAPANESE (JA)
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Semi thesaurus term：
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
All keywords is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
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JST classification (2)：
JST classification
Category name(code) classified by JST.
Artificial intelligence
, Numerical computation
Reference (10)：
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G.E. Hinton and R. Salakhutdinov, “Reducing the dimensionality of data with neural networks,” Science, vol.313, no.5786, pp.504-507, 2006.
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G.E. Hinton, “A practical guide to training restricted boltzmann machines,” Neural networks: Tricks of the trade, pp.599-619, Springer, Berlin, Heidelberg, 2012.
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R. Salakhutdinov and G. Hinton, “Deep boltzmann machines,” Proceedings of the Twelth International Conference on Artificial Intelligence and Statistics, eds. by D. vanDyk and M. Welling, vol.5, pp.448-455, Proceedings of Machine Learning Research, PMLR, Hilton Clearwater Beach Resort, Clearwater Beach, Florida USA, 16-18 Apr 2009. http://proceedings.mlr.press/v5/salakhutdinov09a.html
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G.E. Hinton, “Training products of experts by minimizing contrastive divergence,” Neural Computation, vol.14, pp.1771-1800, 2002.
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M. Opper and O. Winther, “Adaptive and self-averaging thouless-anderson-palmer mean field theory for probabilistic modeling,” Physical Review E, vol.64, p.056131, 2001.
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