%0 Journal Article %1 boustati2020generalized %A Boustati, Ayman %A Akyildiz, Ömer Deniz %A Damoulas, Theodoros %A Johansen, Adam %D 2020 %K bayesian mcmc sampling %T Generalized Bayesian Filtering via Sequential Monte Carlo %U http://arxiv.org/abs/2002.09998 %X 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 generalized 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 through the $\beta$-divergence. Operationalizing the proposed framework is made possible via sequential Monte Carlo methods (SMC). The standard particle methods, and their associated convergence results, are readily generalized to the new setting. We demonstrate our approach to object tracking and Gaussian process regression problems, and observe improved performance over standard filtering algorithms.

@article{boustati2020generalized, 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 generalized 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 through the $\beta$-divergence. Operationalizing the proposed framework is made possible via sequential Monte Carlo methods (SMC). The standard particle methods, and their associated convergence results, are readily generalized to the new setting. We demonstrate our approach to object tracking and Gaussian process regression problems, and observe improved performance over standard filtering algorithms.}, added-at = {2020-02-26T14:17:00.000+0100}, author = {Boustati, Ayman and Akyildiz, Ömer Deniz and Damoulas, Theodoros and Johansen, Adam}, biburl = {https://www.bibsonomy.org/bibtex/2af931fa6b85f90c3e56749cdaa0c01ab/kirk86}, description = {[2002.09998] Generalized Bayesian Filtering via Sequential Monte Carlo}, interhash = {fc9fe51a9304b70a3de949df79964b96}, intrahash = {af931fa6b85f90c3e56749cdaa0c01ab}, keywords = {bayesian mcmc sampling}, note = {cite arxiv:2002.09998}, timestamp = {2020-02-26T14:17:00.000+0100}, title = {Generalized Bayesian Filtering via Sequential Monte Carlo}, url = {http://arxiv.org/abs/2002.09998}, year = 2020 }