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Generalised Bayesian filtering via sequential Monte Carlo
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Boustati, Ayman, Akyildiz, Omar Deniz, Damoulas, Theodoros and Johansen, Adam M. (2020) Generalised Bayesian filtering via sequential Monte Carlo. In: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Virtual conference, 7-12 Dec 2020. Published in: Advances in Neural Information Processing Systems, 33 pp. 418-429.
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WRAP-Generalised-Bayesian-Filtering-sequential-Monte-Carlo-2020.pdf - Accepted Version - Requires a PDF viewer. Download (708Kb) | Preview |
Official URL: https://proceedings.neurips.cc/paper/2020/hash/04e...
Abstract
We introduce a framework for inference in general state-space hidden Markov models (HMMs) under likelihood misspecification. In particular, we leverage the loss-theoretic perspective of Generalized Bayesian Inference (GBI) to define generalised filtering recursions in HMMs, that can tackle the problem of inference under model misspecification. In doing so, we arrive at principled procedures for robust inference against observation contamination by utilising the $\beta$-divergence. Operationalising the proposed framework is made possible via sequential Monte Carlo methods (SMC), where the standard particle methods, and their associated convergence results, are readily adapted to the new setting. We demonstrate our approach to object tracking and Gaussian process regression problems, and observe improved performance over standard filtering algorithms.
| Item Type: | Conference Item (Paper) | ||||||
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| Subjects: | Q Science > QA Mathematics | ||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
| Library of Congress Subject Headings (LCSH): | Bayesian statistical decision theory, Filters (Mathematics), Monte Carlo method | ||||||
| Journal or Publication Title: | Advances in Neural Information Processing Systems | ||||||
| Publisher: | Curran Associates | ||||||
| Official Date: | 2020 | ||||||
| Dates: |
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| Volume: | 33 | ||||||
| Page Range: | pp. 418-429 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||
| Date of first compliant deposit: | 1 October 2020 | ||||||
| Date of first compliant Open Access: | 20 October 2021 | ||||||
| Conference Paper Type: | Paper | ||||||
| Title of Event: | 34th Conference on Neural Information Processing Systems (NeurIPS 2020) | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Virtual conference | ||||||
| Date(s) of Event: | 7-12 Dec 2020 | ||||||
| Related URLs: | |||||||
| Open Access Version: |
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