Rianne de Heide | Bayesian regression with sparse priors

  • When Jul 06, 2016 from 10:00 AM to 11:55 AM (Europe/Amsterdam / UTC200)
  • Where L236
  • Add event to calendar iCal

I intend to cover the basics of Bayesian Ridge regression, the lasso, and the horseshoe prior; and compare their behaviour on sparse data.


Papers:

Carvalho, Polson, Scott - The Horseshoe Estimator for Sparse Signals
faculty.mccombs.utexas.edu/carlos.carvalho/CarvalhoPolsonScott2010.pdf

Park, Casella - The Bayesian Lasso
http://www.stat.ufl.edu/archived/casella/Papers/Lasso.pdf

Damien, Wakefield, Walker - Gibbs sampling for Bayesian non-conjugate and hierarchical models by using auxiliary variables
http://onlinelibrary.wiley.com/doi/10.1111/1467-9868.00179/epdf

Castillo, Schmidt-Hieber, van der Vaart - Bayesian linear regression with sparse priors
https://projecteuclid.org/download/pdfview_1/euclid.aos/1438606851