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SUMMARY:Machine Learning with Quantum Computers - Amira Abbas and Maria Sc
 huld
DTSTART:20220420T100000Z
DTEND:20220420T113000Z
UID:TALK172088@talks.cam.ac.uk
CONTACT:Elre Oldewage
DESCRIPTION:While it is widely believed that quantum computers will outper
 form their classical counterparts in various tasks\, a clear advantage in 
 the realm of machine learning has yet to be defined. In this talk\, we wil
 l discuss the motivation behind using quantum computers for machine learni
 ng tasks and introduce\, at a high level\, some of the leading proposals f
 or quantum machine learning algorithms.\n\nRequired reading: None.\n\nBios
 :\n\nMaria works as a senior researcher for the Toronto-based quantum comp
 uting start-up Xanadu\, where she specialises in the intersection of quant
 um physics and machine learning. She co-authored the book "Machine Learnin
 g with Quantum Computers" (Springer 2018/2021) as well as many papers on q
 uantum machine learning and is a lead developer of the PennyLane software 
 framework for quantum differentiable programming. Maria received her PhD d
 egree in physics from the University of KwaZulu-Natal in 2017\, but also h
 olds a postgraduate degree in political science and spends some of her tim
 e understanding the use of machine learning tools for social sciences rese
 arch.\n\nAmira is a predoc researcher at IBM Zurich\, focusing on quantum 
 machine learning. More specifically\, Amira is investigating the expressib
 ilty of quantum circuits as applied to machine learning models. She is als
 o a Google PhD fellow in quantum computing and is completing her PhD at th
 e University of KwaZulu-Natal.
LOCATION:Cambridge University Engineering Department\, CBL Seminar room BE
 4-38
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