CORDIS Project
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This project aims to enhance control systems in high-dimensional spaces, particularly for applications in autonomous vehicles and precision medicine. By developing new algorithms based on system theory, it seeks to improve the stability and efficiency of learning-based feedback in complex dynamic systems.
In recent years, data-driven control in high dimensions has penetrated into many new application areas.
Examples include control of autonomous vehicles based on video data, simulation based prediction of turbulent flows and precision medicine based on gene sequencing time series data.
Large data sets come with significant computational challenges.
Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamical systems is hampered when the number…
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