activity
20202025
most citedGaussian Process-based Stochastic Model Predictive Control for Overtaking in Autonomous Racing

17 citations · 29 across the 14 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

eess.SY2020

The Impact of Data on the Stability of Learning-Based Control- Extended Version

Armin Lederer, Alexandre Capone, Thomas Beckers +2

Despite the existence of formal guarantees for learning-based control approaches, the relationship between data and control performance is still poorly understood. In this paper, w…

cs.LG2020

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…

cs.LG2020★ 3 cited

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…

eess.SY2020

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…

eess.SY2020

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…