I use these notes as a way to make sure I understand the basic concepts of each topic. I may use them as supplementary materials of graduate courses that I will be teaching. Comments and suggestions are welcome.

A short note on the Bernstein-von Mises theorem under infinite dimensions.

A short note on the causality and its minimax framework.

A short note on the linear form of the Cox model estimator.

A short note on the empirical likelihood and calibration.

A short note on the Frequentist consistency of a nonparametric Bayes.

A short note on the experimental design.

A note on the semi-parametric estimators.

A short note on the adjustment sets.

A short note on the variational inference.

A short note on the Rasch model and latent trait model.

A short note on the mixture of experts.

A short note on the constrained nonparametric quantile regression.

A short note on the effect mediation.

A short note on the coarsening at random.

A short note on the \(L_\infty\) concentration of the KDE.

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