|What aspects of
machine learning and AI benefit the most from quantum
From low polynomial improvements for various aspects of machine learning, reinforcement learning and AI, to more exotic learning algorithms with a potentially BQP-complete flavor, this research line investigates the perspectives and limitations of quantum enhancements for machine learning and AI.
advanced ML and AI techniques be truly integral in building
scalable quantum computers?
Modern machine learning and AI methods may be critical for hard control problems, problems which require on-line and run-time decisions, and may become a vital tool to help us come up with new creative and counter-intuitive solutions to problems which arise in quantum computing.
|How can quantum
computing advance our methods for solving ubiquitous yet
hard computational problems?
Not everything useful has useful lower bounds, and very often, especially in ever more important AI domains, heuristics and in particular quantum heuristic methods will be the only way to go.
In the Quantum@LIACS team we combine the purely theoretical aspects of the questions above, with research in implementations on near-term quantum devices.
More details on my background can be found here.
You can download my (relatively recent) CV
More about my publications can be found here.