PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Switch-Reset Models : Exact and Approximate Inference
Chris Bracegirdle and David Barber
In: AISTATS 2011, 11-13 April 2011, Fort Lauderdale.

Abstract

Reset models are constrained switching latent Markov models in which the dynamics either continues according to a standard model, or the latent variable is resampled. We consider exact marginal inference in this class of models and their extension, the switch-reset models. A further convenient class of conjugateexponential reset models is also discussed. For a length T time-series, exact ltering scales with T^2 and smoothing T^3. We discuss approximate ltering and smoothing routines that scale linearly with T. Applications are given to reset linear dynamical systems.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:7917
Deposited By:David Barber
Deposited On:17 March 2011