On the Dirichlet Prior and Bayesian Regularization
A common objective in learning a model from data is to recover its network structure, while the model parameters are of minor interest. For example, we may wish to recover regulatory networks from high-throughput data sources. In this paper we examine how Bayesian regularization using a Dirichle...
| Main Authors: | , |
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| 语言: | en_US |
| 出版: |
2004
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| 主题: | |
| 在线阅读: | http://hdl.handle.net/1721.1/6702 |