Quantum Machine Learning: What Quantum Computing Means to Data Mining

Quantum Machine Learning: What Quantum Computing Means to Data Mining

by Peter Wittek

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Product Details

ISBN-13: 9780128100400
Publisher: Elsevier Science
Publication date: 09/02/2016
Pages: 176
Product dimensions: 5.98(w) x 9.02(h) x 0.38(d)

About the Author

Peter Wittek received his PhD in Computer Science from the National University of Singapore, and he also holds an MSc in Mathematics. He is interested in interdisciplinary synergies, such as scalable learning algorithms on supercomputers, computational methods in quantum simulations, and quantum machine learning. He collaborated on these topics during research stints to various institutions, including the Indian Institute of Science, Barcelona Supercomputing Center, Bangor University, Tsinghua University, the Centre for Quantum Technologies, and the Institute of Photonic Sciences. He has been involved in major EU research projects, and obtained several academic and industry grants.

Table of Contents

Introduction
Chapter 1: Machine Learning
Chapter 2: Quantum Mechanics
Chapter 3: Quantum Computing
Chapter 4: Unsupervised Learning
Chapter 5: Pattern Recognition and Neural Networks
Chapter 6: Supervised Learning and SUpport Vector Machines
Chapter 7: Regression Analysis
Chapter 8: Boosting
Chapter 9: Clustering Structure and Quantum Computing
Chapter 10: Quantum Pattern Recognition
Chapter 11: Quantum Classification
Chapter 12: Quantum Process Tomography
Chapter 13: Boosting and Adiabatic Quantum Computing

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