[Lisa_seminaires] Alex Shestopaloff, Feb 10, 13:30, AA6214

Junyoung Chung elecegg at gmail.com
Lun 6 Fév 10:52:15 EST 2017


Hi all,

we will have a talk by Alex Shestopaoff on this Friday.
Hope to see many of you there! :)

*Title:* Sampling latent states for high-dimensional non-linear state space
models with the embedded HMM method

*Abstract:* We propose a new scheme for selecting pool states for the
embedded Hidden Markov Model (HMM) Markov Chain Monte Carlo (MCMC) method.
This new scheme allows the embedded HMM method to be used for efficient
sampling of state sequences in state-space models where the state can be
high-dimensional. Previously, embedded HMM methods were only applied to
models with a one-dimensional state space. We demonstrate that using our
proposed pool state selection scheme, an embedded HMM sampler can have
similar performance to a well-tuned sampler that uses a combination of
Particle Gibbs with Backward Sampling (PGBS) and Metropolis updates. The
scaling to higher dimensions is made possible by selecting pool states
locally near the current value of the state sequence. The proposed pool
state selection scheme also allows each iteration of the embedded HMM
sampler to take time linear in the number of the pool states, as opposed to
quadratic as in the original embedded HMM sampler. We also consider a model
with a multimodal posterior, and show how a technique we term ``mirroring''
can be used to efficiently move between the modes. (Joint work with Radford
M. Neal).

*Bio:* Alex has graduated from U. of T (Prof. Radford Neal's group).

Best,
--Junyoung
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