Speaker: Peter Wittek
Affiliation: Institute of Photonic Sciences (ICFO)
Date: Friday, 13 January 2017 at 11:00
Location: Seminar Room, Serrano 121 (CFMAC)
Statistical learning theory is rich in results that changed the way we process and think about data. Furthermore, the theory offered a fresh perspective on artificial intelligence. Applications are countless and much progress has been made in applying learning schemes in quantum control problems. Quantum information processing and quantum computing are the next frontier for machine learning, but benefits work both ways: quantum-enhanced learning is also a promising research direction, but we must generalize known classical results to the quantum case to fully understand the limits and possibilities. This talk gives an introduction to the core concepts in learning theory, and then looks at the major challenges in the intersection of machine learning, artificial intelligence, and quantum information processing.