Learning Theory in the Quantum Universe - IPAM at UCLA

Explore the intersection of quantum mechanics and machine learning in this comprehensive lecture from the Mathematical and Computational Challenges in Quantum Computing Tutorials at IPAM, UCLA. Delve into the fascinating world of learning theory in the quantum universe as presented by Hsin-Yuan Huang (Robert) from Google Quantum AI. Gain insights into how quantum mechanics principles are applied to machine learning algorithms and their potential impact on future computational advancements. Discover the unique challenges and opportunities that arise when classical learning theory meets quantum systems, and understand the implications for quantum computing and artificial intelligence. Engage with cutting-edge concepts and research in this thought-provoking 74-minute talk that bridges the gap between quantum physics and computational learning theory.