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Machine Learning with Quantum Computers

Gebonden Engels 2021 2e druk 9783030830977
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. 

The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.

Specificaties

ISBN13:9783030830977
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer International Publishing
Druk:2

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Inhoudsopgave

<p>Chapter 1. Introduction.- Chapter 2. Machine Learning.- Chapter 3. Quantum Computing.- Chapter 4. Representing Data on a Quantum Computer.- Chapter 5. Variational Circuits as Machine Learning Models.- Chapter 6. Quantum Models as Kernel Methods.- Chapter 7. Fault-Tolerant Quantum Machine Learning.- Chapter 8. Approaches Based on the Ising Model.- Chapter 9. Potential Quantum Advantages.</p>

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        Machine Learning with Quantum Computers