Quantum Machine Learning
- Date: Wednesday 7 February 2018, 16:00 – 17:00
- Location: Roger Stevens LT 22 (10M.22)
- Type: Colloquia
- Cost: Free
Professor Seth Lloyd, Massachusetts Institute of Technology. Part of the theoretical physics colloquium.
Quantum systems are well-known to generate patterns in data that can’t be generated classically. This talk shows that quantum computers and information processors can also recognize and classify patterns that can’t be recognized classically. Because of their ability to perform high-dimensional linear algebra, quantum computers can provide an exponential speed-up over their classical counterparts for a variety of problems in machine learning and data analysis. Examples discussed include principal component analysis, support vector machines, topological analysis, and close by discussing experimental tests of deep quantum learning.
For more information on this event please visit our Theoretical Physics Research Group.