Using Domain Knowledge to Constrain Structure Learning in a Bayesian Bioagent Detector

Abstract

A novel procedure for learning a probabilistic model from mass spectrometry data that accounts for domain specific noise and mitigates the complexity of Bayesian structure learning is presented. We evaluate the algorithm by applying the learned probabilistic model to microorganism detection from mass spectrometry data.

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Cite this paper

@inproceedings{Saksena2005UsingDK, title={Using Domain Knowledge to Constrain Structure Learning in a Bayesian Bioagent Detector}, author={Anshu Saksena and Dennis Lucarelli and I-Jeng Wang}, year={2005} }