Duke Physics Colloquium: Deep Quantum Learning
"Deep Quantum Learning" - Quantum systems can generate patterns in data that can't be generated by any classical system. Can they also recognize and classify patterns that can't be found classically? If classical data can be encoded in quantum states, then quantum computers can be shown to supply exponential speed ups over classical computers for a variety of standard machine learning techniques, such as regression, gradient descent, and support vector machines. This talk addresses the use of quantum computers to perform deep quantum learning, in which adaptive methods of quantum measurement and discrimination are used to find patterns in data. Faculty host: Iman Marvian Refreshments will be available before the event in room 130.
Type: LECTURE/TALK and PANEL/SEMINAR/COLLOQUIUM
Contact: Cristin Paul