BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Maria Schuld (Xanadu\, Toronto\, Canada) DTSTART:20200605T040000Z DTEND:20200605T050000Z DTSTAMP:20260423T010132Z UID:UTSQSI/4 DESCRIPTION:Title: E ncoding Classical Data into Quantum States for Machine Learning\nby Ma ria Schuld (Xanadu\, Toronto\, Canada) as part of Centre for Quantum Softw are and Information Seminar Series\n\n\nAbstract\nWhen quantum computers a re used to process classical data - a setting investigated in the emerging field of quantum machine learning - the first step is to encode data into quantum states. In fact\, this is the most important step: the way we enc ode classical data determines almost entirely the potential power of a qua ntum machine learning algorithm.\nThis talk sheds light on different aspec ts of this data encoding\, from claims of exponential speedups to quantum feature maps and quantum kernel methods.\nIn particular\, it will present the framework of quantum embeddings in which a data encoding can be adapti vely learnt from data\, while the circuit for optimal classification follo ws from well-known results in quantum information theory.\n\nHosted by A/P rof Chris Ferrie\, UTS Centre for Quantum Software and Information.\n LOCATION:https://researchseminars.org/talk/UTSQSI/4/ END:VEVENT END:VCALENDAR