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Baysian Nonparametrics via Neural Networks (ASA-SIAM Series on Statistics and Applied Probability)

Herbert K. H. Lee




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 | #3257807 in Books |  SIAM: Society for Industrial and Applied Mathematics |  2004-07-08 | Original language:English | PDF # 1 |  8.98 x.28 x5.98l,1.10 | File type: PDF | 104 pages

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||About the Author|Herbert K. H. Lee is an Assistant Professor of Applied Mathematics and Statistics at the University of California, Santa Cruz. His major research interest is in the field of Bayesian statistics, with primary emphases on spatial inverse problems

Bayesian Nonparametrics via Neural Networks is the first book to focus on neural networks in the context of nonparametric regression and classification, working within the Bayesian paradigm. It discusses neural networks in a statistical context, an approach in contrast to existing books, which tend to treat neural networks as a machine learning algorithm instead of a statistical model. Once this underlying statistical model is recognized, other standard statistical techn...

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