Jens Eisert, Klaus-Robert Müller
Frederik Wilde (FU)
01.01.2019 – 31.12.2021
One of the core tools used and developed in MATH+ is that of machine learning. This project suggests a concerted research program in a highly promising and novel kind of machine learning, that of quantum machine learning, in several flavors. Emphasis is on mathematical and conceptual method development, coordinated and in collaboration with other machine learning efforts in MATH+, taking a rigorous perspective. Results along these line of thought are improved quantum stochastic gradient methods with full recovery guarantees. However, a range of applications, ranging from communication technology to condensed-matter physics, will be explored as well.
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