ML Anthology

The Sample Complexity of Learning Fixed-Structure Bayesian Networks

Sanjoy Dasgupta
MLJ 1997 pp. 165-180
doi:10.1023/A:1007417612269 /mlj/1997/dasgupta1997mlj-sample/

Abstract

We consider the problem of PAC learning probabilistic networks in the case where the structure of the net is specified beforehand. We allow the conditional probabilities to be represented in any manner (as tables or specialized functions) and obtain sample complexity bounds for learning nets with and without hidden nodes.

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Text

Dasgupta. "The Sample Complexity of Learning Fixed-Structure Bayesian Networks." Machine Learning, 1997. doi:10.1023/A:1007417612269

Markdown

[Dasgupta. "The Sample Complexity of Learning Fixed-Structure Bayesian Networks." Machine Learning, 1997.](https://mlanthology.org/mlj/1997/dasgupta1997mlj-sample/) doi:10.1023/A:1007417612269

BibTeX

@article{dasgupta1997mlj-sample,
  title     = {{The Sample Complexity of Learning Fixed-Structure Bayesian Networks}},
  author    = {Dasgupta, Sanjoy},
  journal   = {Machine Learning},
  year      = {1997},
  pages     = {165-180},
  doi       = {10.1023/A:1007417612269},
  volume    = {29},
  url       = {https://mlanthology.org/mlj/1997/dasgupta1997mlj-sample/}
}