Machine Learning Coffee seminar: Aki Vehtari, Aalto University
Weekly seminars held jointly by Aalto University and the University of Helsinki.
Helsinki region machine learning researchers will start our week by an exciting machine learning talk. The aim is to gather people from different fields of science with interest in machine learning. Porridge and coffee is served at 9:00 and the talk will begin at 9:15. The venue for this talk is seminar room Exactum D123, Kumpula.
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On Priors and Bayesian Variable Selection in Large p, Small n Regression
Professor of Computer Science, Aalto University
The Bayesian approach is well known for using priors to improve inference, but equally important part is the integration over the uncertainties. I first present recent development in hierarchical shrinkage priors for presenting sparsity assumptions in covariate effects. I then present a projection predictive variable selection approach, which is a Bayesian decision theoretical approach for variable selection which can preserve the essential information and uncertainties related to all variables in the study. I also present recent excellent experimental results and easy to use software.
See the next talks at the seminar webpage.
Please spread the news and join us for our weekly habit of beginning the week by an interesting machine learning talk!