SMS scnews item created by Tiangang Cui at Thu 5 Sep 2024 1557
Type: Seminar
Distribution: World
Expiry: 5 Sep 2025
Calendar1: 13 Sep 2024 1300-1400
CalLoc1: Carslaw 275
CalTitle1: Tensor-Train Methods for Sequential State and Parameter Estimation in State-Space Models
Auth: tcui@ptcui.pc (assumed)

Statistics Seminar

Tensor-Train Methods for Sequential State and Parameter Estimation in State-Space Models

Zhao

The next statistics seminar will be presented by Dr Yiran Zhao from School of Mathematics and Statistics.

Title: Tensor-Train Methods for Sequential State and Parameter Estimation in State-Space Models
Speaker: Yiran Zhao
Time and location : 1-2pm on Carslaw 275 or Zoom
Abstract :

Numerous real-world applications require the estimation, forecasting, and control of dynamic systems using incomplete and indirect observations. These problems can be formulated as state-space models, where the challenge lies in learning the model states and parameters from observed data. We present new tensor-based sequential Bayesian learning methods that jointly estimate parameters and states. Our methods provide manageable error analysis and potentially mitigate the particle degeneracy encountered in many particle-based approaches. Besides offering new insights into algorithmic design, our methods naturally incorporate conditional transports, enabling filtering, smoothing, and parameter estimation within a unified framework.