For all Bayesians and sympathisers in the Paris area, All about that Bayes seminars are restarting this semester with a talk by Kaniav Kamari (Centrale Supélec) on 10 October, 16h00, on Campus Pierre & Marie Curie, SCAI:
Bayesian principal component analysis
The technique of principal component analysis (PCA) has recently been expressed as the maximum likelihood solution for a generative latent variable model. In this talk, I’ll first present probabilistic reformulation that is the basis for a Bayesian treatment of PCA. Then, my focus will be on showing that the effective dimensionality of the latent space (equivalent to the number of retained principal components) can be determined automatically as part of the Bayesian inference procedure.
