Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation-Reference-Cited by-同舟云学术

Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation

Published:2013 Issue: Volume: Page:596-611
ISSN:0302-9743
Container-title:Advanced Information Systems Engineering
language:
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Author:

Liu Song,Quinn John A.,Gutmann Michael U.,Sugiyama Masashi

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-40991-2_38

Reference22 articles.

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3. Koller, D., Friedman, N.: Probabilistic graphical models: principles and techniques. MIT Press (2009)

4. Ravikumar, P., Wainwright, M.J., Lafferty, J.D.: High-dimensional ising model selection using ℓ1-regularized logistic regression. The Annals of Statistics 38(3), 1287–1319 (2010)

5. Lee, S.I., Ganapathi, V., Koller, D.: Efficient structure learning of Markov networks using l 1-regularization. In: Schölkopf, B., Platt, J., Hoffman, T. (eds.) Advances in Neural Information, vol. 19, pp. 817–824. MIT Press, Cambridge (2007)

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