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Cookie akzeptierenSriraam Natarajan / Jude Shavlik / Tushar Khot / Kristian Kersting
Boosted Statistical Relational Learners
- Springer International Publishing
- 2015
- Taschenbuch
- 84 Seiten
- ISBN 9783319136431
This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications. The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in
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