Part I: General Topics
- The way we read and present academic work
- A brief language guide for statistical writing
- The structure of statistical papers
- Typesetting your manuscript
Part II: Statistical Topics
Guide for presentations
You are supposed to work as a team (2-4 people) for each presentation topic. Please reply below to select the topic (with “Presentation Topic”) you want to present. This work counts 50% of your final score.
- Presentation Topic (Nov 20): Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. the Journal of machine Learning research, 3, 993-1022.
- Presentation Topic (Nov 27): Blei, D. M., & Lafferty, J. D. (2006). Dynamic topic models. In Proceedings of the 23rd international conference on Machine learning (pp. 113-120). ACM.
- Lecture (Dec 4): Introduction to Bayesian Inference
- Presentation Topic (Dec 11): Mcauliffe, J. D., & Blei, D. M. (2008). Supervised topic models. In Advances in neural information processing systems (pp. 121-128).
- Presentation Topic (Dec 18): Blei, D., & Lafferty, J. (2006). Correlated topic models. Advances in neural information processing systems, 18, 147.
- Presentation Topic (Dec 25): Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M. (2006). Hierarchical dirichlet processes. Journal of the American Statistical Association, 101(476).
- Presentation Topic (Jan 8): Blei, D. M., & Jordan, M. I. (2006). Variational inference for Dirichlet process mixtures. Bayesian analysis, 1(1), 121-143.
- Presentation Topic (Jan 15): Hoffman, M. D., Blei, D. M., Wang, C., & Paisley, J. (2013). Stochastic variational inference. The Journal of Machine Learning Research, 14(1), 1303-1347.