Quantum algorithms for machine learning

Machine learning is one of the most promising applications of quantum algorithms. This area was pioneered by the HHL algorithm that in some cases can solve systems of linear equations exponentially faster than is possible classically. Since then many quantum machine learning applications have appeared, including by consortium members on efficient Recommendation Systems and Gradient Descent. Our aim is to design novel quantum algorithms for machine learning applications and analyse their performance in practice.

Work package Leader: Cyril Allouche (Atos – Bull SAS)