4 papers
Theoretical guarantees for lifted samplers
Philippe Gagnon, Florian Maire
Lifted samplers form a class of Markov chain Monte Carlo methods which has drawn a lot attention in recent years due to superior performance in challenging Bayesian applications. A…
Reconciling Bayesian and frequentist approaches to robustness against outliers
Philippe Gagnon, Alain Desgagné
Heavy-tailed models are used as a way to gain robustness against outliers in Bayesian analyses. In frequentist analyses, M-estimators are often employed. In this paper, the two app…
Simple proof of robustness for Bayesian heavy-tailed linear regression models
Philippe Gagnon
In the Bayesian literature, a line of research called resolution of conflict is about the characterization of robustness against outliers of statistical models. The robustness char…
Exponential Convergence of CAVI for Bayesian PCA
Arghya Datta, Philippe Gagnon, Florian Maire
Probabilistic principal component analysis (PCA) and its Bayesian variant (BPCA) are widely used for dimension reduction in machine learning and statistics. The main advantage of p…