4 papers
Adaptive prediction theory combining offline and online learning
Haizheng Li, Lei Guo
Real-world intelligence systems usually operate by combining offline learning and online adaptation with highly correlated and non-stationary system data or signals, which, however…
Asymptotically efficient adaptive identification under saturated output observation
Lantian Zhang, Lei Guo
As saturated output observations are ubiquitous in practice, identifying stochastic systems with such nonlinear observations is a fundamental problem across various fields. This pa…
Adaptive Tracking Control with Binary-Valued Output Observations
Lantian Zhang, Lei Guo
This paper considers real-time control and learning problems for finite-dimensional linear systems under binary-valued and randomly disturbed output observations. This has long bee…
Koopman-based Control for Stochastic Systems: Application to Enhanced Sampling
Lei Guo, Jan Heiland, Feliks Nüske
We present a data-driven approach to use the Koopman generator for prediction and optimal control of control-affine stochastic systems. We provide a novel conceptual approach and a…