C. N. Liu’s scientific contributions

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Publications (1)

Liu, C.: Approximating Discrete Probability Distributions with Dependence Trees. IEEE Transactions on Information Theory 14(3), 462-467
  • Article

June 1968

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315 Reads

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2,131 Citations

IEEE Transactions on Information Theory

C. K. Chow

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C. N. Liu

A method is presented to approximate optimally an n -dimensional discrete probability distribution by a product of second-order distributions, or the distribution of the first-order tree dependence. The problem is to find an optimum set of n - 1 first order dependence relationship among the n variables. It is shown that the procedure derived in this paper yields an approximation of a minimum difference in information. It is further shown that when this procedure is applied to empirical observations from an unknown distribution of tree dependence, the procedure is the maximum-likelihood estimate of the distribution.

Citations (1)

... In a special case, if any random variable is causally dependent on only one random variable, the Bayesian network structure can be represented as a directed branching tree. In this case, Chow and Liu [26] proposed an algorithm to construct the Bayesian network as the maximum spanning tree from the pair-wise mutual information of all possible pairs. Generally, a Bayesian network with no loop structure is called a polytree. ...

Reference:

Tensor tree learns hidden relational structures in data to construct generative models
Liu, C.: Approximating Discrete Probability Distributions with Dependence Trees. IEEE Transactions on Information Theory 14(3), 462-467
  • Citing Article

  • June 1968

IEEE Transactions on Information Theory

C. K. Chow

·

C. N. Liu