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→互信息的贝叶斯估计 Bayesian estimation of mutual information
It is well-understood how to do Bayesian estimation of the mutual information of a joint distribution based on samples of that distribution.
It is well-understood how to do Bayesian estimation of the mutual information of a joint distribution based on samples of that distribution.
如何根据联合分布的样本对联合分布的互信息进行贝叶斯估计，是很容易理解的。
The first work to do this, which also showed how to do Bayesian estimation of many other information-theoretic properties besides mutual information, was <ref>{{cite journal | last1 = Wolpert | first1 = D.H. | last2 = Wolf | first2 = D.R. | year = 1995 | title = Estimating functions of probability distributions from a finite set of samples | journal = Physical Review E | volume = 52 | issue = 6 | pages = 6841–6854 | doi = 10.1103/PhysRevE.52.6841 | pmid = 9964199 | citeseerx = 10.1.1.55.7122 | bibcode = 1995PhRvE..52.6841W }}</ref>. Subsequent researchers have rederived <ref>{{cite journal | last1 = Hutter | first1 = M. | year = 2001 | title = Distribution of Mutual Information | journal = Advances in Neural Information Processing Systems 2001 }}</ref>
The first work to do this, which also showed how to do Bayesian estimation of many other information-theoretic properties besides mutual information, was <ref>{{cite journal | last1 = Wolpert | first1 = D.H. | last2 = Wolf | first2 = D.R. | year = 1995 | title = Estimating functions of probability distributions from a finite set of samples | journal = Physical Review E | volume = 52 | issue = 6 | pages = 6841–6854 | doi = 10.1103/PhysRevE.52.6841 | pmid = 9964199 | citeseerx = 10.1.1.55.7122 | bibcode = 1995PhRvE..52.6841W }}</ref>. Subsequent researchers have rederived <ref>{{cite journal | last1 = Hutter | first1 = M. | year = 2001 | title = Distribution of Mutual Information | journal = Advances in Neural Information Processing Systems 2001 }}</ref>