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Bayesian sparse factor models and DAGs inference and comparison

Publication ,  Conference
Henao, R; Winther, O
Published in: Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference
January 1, 2009

In this paper we present a novel approach to learn directed acyclic graphs (DAGs) and factor models within the same framework while also allowing for model comparison between them. For this purpose, we exploit the connection between factor models and DAGs to propose Bayesian hierarchies based on spike and slab priors to promote sparsity, heavy-tailed priors to ensure identifiability and predictive densities to perform the model comparison. We require identifiability to be able to produce variable orderings leading to valid DAGs and sparsity to learn the structures. The effectiveness of our approach is demonstrated through extensive experiments on artificial and biological data showing that our approach outperform a number of state of the art methods.

Duke Scholars

Published In

Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference

ISBN

9781615679119

Publication Date

January 1, 2009

Start / End Page

736 / 744
 

Citation

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Henao, R., & Winther, O. (2009). Bayesian sparse factor models and DAGs inference and comparison. In Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference (pp. 736–744).
Henao, R., and O. Winther. “Bayesian sparse factor models and DAGs inference and comparison.” In Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference, 736–44, 2009.
Henao R, Winther O. Bayesian sparse factor models and DAGs inference and comparison. In: Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 2009. p. 736–44.
Henao, R., and O. Winther. “Bayesian sparse factor models and DAGs inference and comparison.” Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference, 2009, pp. 736–44.
Henao R, Winther O. Bayesian sparse factor models and DAGs inference and comparison. Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference. 2009. p. 736–744.

Published In

Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference

ISBN

9781615679119

Publication Date

January 1, 2009

Start / End Page

736 / 744