1. Lecture Notes in Computer Science;L Biewald,2012
2. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. Journal of Machine Learning Research 3, 993–1022 (2003)
3. Bleier, A.: Practical collapsed stochastic variational inference for the hdp. In: NIPS Workshop on Topic Models: Computation, Application, and Evaluation (2013)
4. Chang, J., Boyd-Graber, J.L., Gerrish, S., Wang, C., Blei, D.M.: Reading tea leaves: how humans interpret topic models. In: Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held December 7–10, 2009, Vancouver, British Columbia, Canada, pp. 288–296 (2009)
5. Foulds, J.R., Boyles, L., DuBois, C., Smyth, P., Welling, M.: Stochastic collapsed variational bayesian inference for latent dirichlet allocation. In: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, pp. 446–454, August 11–14, 2013