Patrick Stinson: May 20th

Abstract: I'll present Lindsten and Schoen's review of SMC-based backward simulation methods. The most immediate application of backward simulation is to address state smoothing problems in sequential models; however, this method can be generalized to non-Markovian latent variable models. Particle MCMC is a new method that incorporates SMC-based proposal schemes into MCMC algorithms. Backward simulation and a related method, ancestral sampling, can dramatically increase particle efficiency and mixing in this setting. Paper: "Backward Simulation Methods for Monte Carlo Statistical Inference" by Fredrik Lindsten and Thomas B. Schoen Link: http://users.isy.liu.se/en/rt/lindsten/publications/LindstenS_2013.pdf

Josh Merel: May 13th

Josh will give a recap of interesting happenings from the recent International Conference on Learning Representations (ICLR).