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References Zou,H.,and Hastie,T.2005.Regularization and variable Archambeau,C.,and Bach,F.2008.Sparse probabilistic selection via the elastic net.Journal of the Royal Statistical projections.In NIPS 21. Society,Series B 67(2):301-320. Caron,F,and Doucet,A.2008.Sparse Bayesian nonpara- Zou,H.;Hastie,T.;and Tibshirani,R.2006.Sparse prin- metric regression.In ICML. cipal component analysis.Journal of Computational and Graphical Statistics 15(2):265-286. Craven,M.;DiPasquo,D.;Freitag,D.:McCallum,A.; Mitchell,T.M.;Nigam,K.;and Slattery,S.1998.Learning to extract symbolic knowledge from the world wide web.In AAAI/IAAI. Dempster,A.;Laird,N.;and Rubin,D.1977.Maximum likelihood from incomplete data via the EM algorithm.Jour- nal of the Royal Statistical Society,Series B 39(1):1-38. Figueiredo,M.A.T.2003.Adaptive sparseness for su- pervised learning.IEEE Trans.Pattern Anal.Mach.Intell. 25(9):1150-1159 Getoor,L..and Taskar,B.2007.Introduction to Statistical Relational Learning.The MIT Press. 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McCallum,A.;Nigam,K.;Rennie,J.;and Seymore,K. 2000.Automating the construction of internet portals with machine learning.Information Retrieval 3(2):127-163. Park.T..and Casella.G.2008.The Bayesian lasso.Journal of the American Statistical Association 103(482):681-686. Sigg,C.D.,and Buhmann,J.M.2008.Expectation- maximization for sparse and non-negative PCA.In ICML. Tipping,M.E.,and Bishop,C.M.1999.Probabilistic prin- cipal component analysis.Journal of the Royal Statistical Society,Series B 61(3):611-622. Zhu,S.;Yu,K.;Chi,Y.;and Gong,Y.2007.Combining content and link for classification using matrix factorization. In SIGIR.References Archambeau, C., and Bach, F. 2008. Sparse probabilistic projections. In NIPS 21. Caron, F., and Doucet, A. 2008. Sparse Bayesian nonpara￾metric regression. In ICML. Craven, M.; DiPasquo, D.; Freitag, D.; McCallum, A.; Mitchell, T. M.; Nigam, K.; and Slattery, S. 1998. Learning to extract symbolic knowledge from the world wide web. In AAAI/IAAI. Dempster, A.; Laird, N.; and Rubin, D. 1977. Maximum likelihood from incomplete data via the EM algorithm. Jour￾nal of the Royal Statistical Society, Series B 39(1):1–38. Figueiredo, M. A. T. 2003. Adaptive sparseness for su￾pervised learning. IEEE Trans. Pattern Anal. Mach. Intell. 25(9):1150–1159. Getoor, L., and Taskar, B. 2007. Introduction to Statistical Relational Learning. The MIT Press. Guan, Y., and Dy, J. G. 2009. Sparse probabilistic principal component analysis. In AISTATS. Gupta, A. K., and Nagar, D. K. 2000. Matrix Variate Distri￾butions. Chapman & Hall/CRC. Jolliffe, I. T. 2002. Principal Component Analysis. Springer, second edition. Jordan, M. I.; Ghahramani, Z.; Jaakkola, T.; and Saul, L. K. 1999. An introduction to variational methods for graphical models. Machine Learning 37(2):183–233. Li, W.-J., and Yeung, D.-Y. 2009. Relation regularized ma￾trix factorization. In IJCAI. Li, W.-J., and Yeung, D.-Y. 2011. Social relations model for collaborative filtering. In AAAI. Li, W.-J.; Yeung, D.-Y.; and Zhang, Z. 2009. Probabilistic relational PCA. In NIPS 22. Li, W.-J.; Yeung, D.-Y.; and Zhang, Z. 2011. Generalized latent factor models for social network analysis. In IJCAI. Li, W.-J.; Zhang, Z.; and Yeung, D.-Y. 2009. Latent Wishart processes for relational kernel learning. In AISTATS. Li, W.-J. 2010. Latent Factor Models for Statistical Rela￾tional Learning. Ph.D. Dissertation, Hong Kong University of Science and Technology. McCallum, A.; Nigam, K.; Rennie, J.; and Seymore, K. 2000. Automating the construction of internet portals with machine learning. Information Retrieval 3(2):127–163. Park, T., and Casella, G. 2008. The Bayesian lasso. Journal of the American Statistical Association 103(482):681–686. Sigg, C. D., and Buhmann, J. M. 2008. Expectation￾maximization for sparse and non-negative PCA. In ICML. Tipping, M. E., and Bishop, C. M. 1999. Probabilistic prin￾cipal component analysis. Journal of the Royal Statistical Society, Series B 61(3):611–622. Zhu, S.; Yu, K.; Chi, Y.; and Gong, Y. 2007. Combining content and link for classification using matrix factorization. In SIGIR. Zou, H., and Hastie, T. 2005. Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society, Series B 67(2):301–320. Zou, H.; Hastie, T.; and Tibshirani, R. 2006. Sparse prin￾cipal component analysis. Journal of Computational and Graphical Statistics 15(2):265–286
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