Kernel Principal Component Analysis, Spectral Clustering, Gaussian Processes, RKHS of vector-valued functions,
RKHS embedding of the realization of random variables, Tests of independence and conditional independence, Bayesian networks, k-means, mixture models, the expectation maximization algorithm, Markov random fields, Gibbs distributions, belief propagation algorithms, variational inference, Markov chain Monte Carlo.