Supervised Learning with Quantum Computers

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Supervised Learning with Quantum Computers

Condensed matter physics (liquid state and solid state physics) Quantum physics (quantum mechanics and quantum field theory) Mathematical physics Materials science Mathematical theory of computation Artificial intelligence Pattern recognition

Authors: Maria Schuld, Francesco Petruccione

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Collection: Quantum Science and Technology

Language: English

Published by: Springer

Published on: 30th August 2018

Format: LCP-protected ePub

Size: 9 Mb

ISBN: 9783319964249


Quantum Machine Learning

Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The book summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine quantum learning models. A special focus lies on supervised learning, and applications for near-term quantum devices.

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