3 citations · 3 across the 1 of their papers we have counts for
4 papers
Anticipating the Long-Term Effect of Online Learning in Control
Alexandre Capone, Sandra Hirche
Control schemes that learn using measurement data collected online are increasingly promising for the control of complex and uncertain systems. However, in most approaches of this…
Localized active learning of Gaussian process state space models
Alexandre Capone, Jonas Umlauft, Thomas Beckers +2
The performance of learning-based control techniques crucially depends on how effectively the system is explored. While most exploration techniques aim to achieve a globally accura…
How Training Data Impacts Performance in Learning-based Control
Armin Lederer, Alexandre Capone, Jonas Umlauft +1
When first principle models cannot be derived due to the complexity of the real system, data-driven methods allow us to build models from system observations. As these models are e…
Data selection for multi-task learning under dynamic constraints
Alexandre Capone, Armin Lederer, Jonas Umlauft +1
Learning-based techniques are increasingly effective at controlling complex systems using data-driven models. However, most work done so far has focused on learning individual task…