Privacy-sensitive Bayesian network parameter learning

  title={Privacy-sensitive Bayesian network parameter learning},
  author={Da Meng and Krishnamoorthy Sivakumar and Hillol Kargupta},
  journal={Fourth IEEE International Conference on Data Mining (ICDM'04)},
This paper considers the problem of learning the parameters of a Bayesian network, assuming the structure of the network is given, from a privacy-sensitive dataset that is distributed between multiple parties. For a binary-valued dataset, we show that the count information required to estimate the conditional probabilities in a Bayesian network can be obtained as a solution to a set of linear equations involving some inner product between the relevant different feature vectors. We consider a… CONTINUE READING
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