A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation

[edit]

Ramin Raziperchikolaei, Harish Bhat ;
Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5380-5388, 2019.

Abstract

We propose and analyze a block coordinate descent proximal algorithm (BCD-prox) for simultaneous filtering and parameter estimation of ODE models. As we show on ODE systems with up to d=40 dimensions, as compared to state-of-the-art methods, BCD-prox exhibits increased robustness (to noise, parameter initialization, and hyperparameters), decreased training times, and improved accuracy of both filtered states and estimated parameters. We show how BCD-prox can be used with multistep numerical discretizations, and we establish convergence of BCD-prox under hypotheses that include real systems of interest.

Related Material