[Turing-Southampton] Fw: S3RI seminar: Alexander Shestopaloff, Thursday 22 October 2-3pm

[Sam Collins]

Dear all,

Hope you've all been having a nice week.

Just a reminder of the S3RI seminar scheduled for this afternoon at 2 pm, we have Dr Alexander Shestopaloff (Queen Mary University of London) speaking to us about

"Scaling Monte Carlo inference for State-Space Models".

Please see below for further details for the talk.


Hope to see you there later today!


Kind regards,

Jessie



Title: Scaling Monte Carlo inference for State-Space Models

Alexander Shestopaloff (Queen Mary University of London)

The iterated conditional Sequential Monte Carlo (cSMC) method is a particle MCMC method commonly used for state inference in non-linear, non-Gaussian state space models. Standard implementations of iterated cSMC provide an efficient way to sample state sequences in low-dimensional state space models. However, efficiently scaling iterated cSMC methods to perform well in models with a high-dimensional state remains a challenge. One reason for this is the use of a global proposal, without reference to the current state sequence. In high dimensions, such a proposal will typically not be well-matched to the posterior and impede efficient sampling. I will describe a technique based on the embedded HMM (Hidden Markov Model) framework to construct efficient proposals in high dimensions that are local relative to the current state sequence. A second obstacle to scalability of iterated cSMC is not using the entire observed sequence to construct the proposal. Typical implementations of iterated cSMC use a proposal at time t that relies only on data up to time t, even when data after time t is available. In high dimensions and in the presence of informative data, such proposals can become inefficient and slow down sampling. I will introduce a principled approach to incorporating all data in the cSMC proposal at time t. By considering several examples, I will demonstrate that both strategies improve the performance of iterated cSMC for state sequence sampling in high-dimensional state space models.

For the current schedule of S3RI seminars, see https://tinyurl.com/s3riseminar<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftinyurl.com%2Fs3riseminar&data=04%7C01%7C%7Ca55e60a6e8a44cec238f08d8767bfcc9%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637389622175719905%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=EmpmDyCnZmkqzNMidghKk3%2FF1gI3nkMYe1QvaMaEAY4%3D&reserved=0>


If you haven't joined yet, but would like to join the S3RI team on Microsoft Teams please use the link below:

https://teams.microsoft.com/l/team/19%3a71f0ed99e3ce45219eef73b9cbd1b0f3%40thread.tacv2/conversations?groupId=260706f2-7819-4bfe-920a-3d55825d8e9c&tenantId=4a5378f9-29f4-4d3e-be89-669d03ada9d8
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