[3] D. Bertsekas. Nonlinear Programming. Athena Scientific, 1999.
4] D. Blei and J. Lafferty. A correlated topic model of Science. Annals of Applied Statistics, 1(1):17–35, 2007.
[5] D. Blei and J. Lafferty. Topic models. In A. Srivastava and M. Sahami, editors, Text Mining: Theory and Applications. Taylor and Francis, 2009.
[6] D. Blei and J. McAuliffe. Supervised topic models. In Neural Information Processing Systems, 2007.
[7] D. Blei, A. Ng, and M. Jordan. Latent Dirichlet allocation. Journal of Machine Learning Research, 3:993–1022, January 2003.
[8] J. Chang, J. Boyd-Graber, S. Gerrish, C. Wang, and D. Blei. Reading tea leaves: How humans interpret topic models. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 288–296, 2009.
[9] A. Dempster, N. Laird, and D. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B, 39:1–38, 1977.
[10] S. M. Gerrish and D. M. Blei. Predicting legislative roll calls from text. In Proceedings of the 28th Annual International Conference on Machine Learning, ICML ’11, 2011.
[11] J. L. Herlocker, J. A. Konstan, A. Borchers, and J. Riedl. An algorithmic framework for performing collaborative filtering. In Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’99, pages 230–237, New York, NY, USA, 1999. ACM.
[12] Y. Hu, Y. Koren, and C. Volinsky. Collaborative filtering for implicit feedback datasets. In Proceedings of the 2008 Eighth IEEE International Conference on Data Mining, pages 263–272, Washington, DC, USA, 2008. IEEE Computer Society.
[13] Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. IEEE Computer, 42(8):30–37, 2009.
[14] P. Melville, M. R., and R. Nagaraja. Content-boosted collaborative filtering for improved recommendations. In American Association for Artificial Intelligence, pages 187–192, 2002.
[15] R. J. Mooney and L. Roy. Content-based book recommending using learning for text categorization. In Proceedings of the fifth ACM conference on Digital libraries, pages 195–204, New York, NY, USA, 2000. ACM.
[16] R. Pan, Y. Zhou, B. Cao, N. N. Liu, R. Lukose, M. Scholz, and Q. Yang. One-class collaborative filtering. In Proceedings of the 2008 Eighth IEEE International Conference on Data Mining, pages 502–511, Washington, DC, USA, 2008. IEEE Computer Society.
[17] R. Salakhutdinov and A. Mnih. Bayesian probabilistic matrix factorization using Markov chain Monte Carlo. In Proceedings of the 25th International Conference on Machine learning, pages 880–887. ACM, 2008.
[18] R. Salakhutdinov and A. Mnih. Probabilistic matrix