ML Anthology

Data Compression for Learning MRF Parameters

Khaled S. Refaat, Adnan Darwiche
IJCAI 2015 pp. 3784-3790
/ijcai/2015/refaat2015ijcai-data/

Abstract

We propose a technique for decomposing and compressing the dataset in the parameter learning problem in Markov random fields. Our technique applies to incomplete datasets and exploits variables that are always observed in the given dataset. We show that our technique allows exact computation of the gradient and the likelihood, and can lead to orders-of-magnitude savings in learning time.

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Cite

Text

Refaat and Darwiche. "Data Compression for Learning MRF Parameters." International Joint Conference on Artificial Intelligence, 2015.

Markdown

[Refaat and Darwiche. "Data Compression for Learning MRF Parameters." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/refaat2015ijcai-data/)

BibTeX

@inproceedings{refaat2015ijcai-data,
  title     = {{Data Compression for Learning MRF Parameters}},
  author    = {Refaat, Khaled S. and Darwiche, Adnan},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {3784-3790},
  url       = {https://mlanthology.org/ijcai/2015/refaat2015ijcai-data/}
}