Quantum algorithms for data analysis
1
Preface
1.1
Abstract
1.2
Changelog
1.3
Teaching using this book
2
Classical data in quantum computers
3
Classical machine learning
4
A useful toolbox
4.1
Phase estimation
4.2
Grover’s algorithm, amplitude games
4.2.1
Example: estimating average and variance of a function
4.3
Finding the minimum
4.4
Quantum linear algebra
4.5
Linear combination of unitaries
4.6
Singular value transformation
4.7
Distances, inner products, norms, and quadratic forms
4.7.1
Inner products and quadratic forms with KP-trees
4.7.2
Inner product and l1-norm estimation with query access
4.8
Hamiltonian simulation
4.8.1
Introduction to Hamiltonians
I Quantum Machine Learning
5
Quantum perceptron
6
SVE-based quantum algorithms
7
Quantum algorithms for Monte Carlo
8
Dimensionality reduction
9
q-means
10
Quantum Expectation-Maximization
11
QML on real datasets
12
Quantum algorithms for graph problems
13
Lower bounds on query complexity of quantum algorithms
II Everything else
14
Selected works on quantum algorithms
15
Solutions to exercises
Appendix
A
Contributions and acknowledgements
A.1
License and citation
A.2
Cookie Policy
B
References
By Alessandro 'Scinawa' Luongo
Quantum algorithms for data analysis
Chapter 6
SVE-based quantum algorithms
Contributors: Alessandro Luongo, Armando Bellante
Translation: