Bayesian Sequential Estimation

Robust Sequential Approximate Bayesian Estimation

An approximation tothe sequential updating of the distribution flocation parameters of a linear time series model is developed for non-normal observations. The behaviour of the resulting non-linear recursive filtering algorithm isexamined and shown to have certain desirable properties for a variety of non-normal error distributions. Illustrative examples are given and relationships with previou...

Sequential Bayesian Estimation And Model Selection Applied To Neural Networks

Computational intelligence sequential Monte Carlos for recursive Bayesian estimation

Recursive Bayesian estimation using sequential Monte Carlos methods is a powerful numerical technique to understand latent dynamics of non-linear non-Gaussian dynamical systems. Classical sequential Monte Carlos suffer from weight degeneracy which is where the number of distinct particles collapse. Traditionally this is addressed by resampling, which effectively replaces high weight particles w...

on the bayesian sequential change-point detection

the problems of sequential change-point have several important applications in quality control, signal processing, and failure detection in industry and finance. we discuss a bayesian approach in the context of statistical process control: at an unknown time $tau$, the process behavior changes and the distribution of the data changes from p0 to p1. two cases are considered: (i) p0 and p1 are fu...

Sequential Bayesian Search

Millions of people search daily for movies, music, and books on the Internet. Unfortunately, non-personalized exploration of items can result in an infeasible number of costly interaction steps. We study the problem of efficient, repeated interactive search. In this problem, the user is navigated to the items of interest through a series of options and our objective is to learn a better search ...