读Learning belief networks from empirical data
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在看Neal, R.M., Connectionist learning of belief networks. Artif. Intell.},
issue_date = {July 1992, 1992. 56(1): p. 71--113.
5.Learning belief networks from empirical data
有训练集T,每个元素有些2值的属性,
决定状态向量S,<V可见的,H隐藏的>。
用梯度方法,最大似然L。
6. Representational power of belief networks
表示总体分布
4个及以上的点,boltzmann machines和sigmoid belief networks可以表示对方表示不了的啦。
表示混合的分布,用隐藏的点,表示可见点的分布,是"mixtures".
- 读Learning belief networks from empirical data
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