Advances in quantum machine learning

Abstract

Here we discuss advances in the field of quantum machine learning. The following document offers a hybrid discussion; both reviewing the field as it is currently, and suggesting directions for further research. We include both algorithms and experimental implementations in the discussion. The field's outlook is generally positive, showing significant promise. However, we believe there are appreciable hurdles to overcome before one can claim that it is a primary application of quantum computation.

arXiv comment38 pages, 17 Figures

References in corpus (36)

• Quantum Machine Learning
• Quantum Mechanics helps in searching for a needle in a haystack
• Quantum algorithm for solving linear systems of equations
• Surface codes: Towards practical large-scale quantum computation
• Quantum support vector machine for big data classification
• Quantum principal component analysis
• Quantum random access memory
• Quantum annealing with more than one hundred qubits
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• A Robust Quantum Random Access Memory
• Hidden Quantum Markov Models and non-adaptive read-out of many-body states
• Local Realistic Model for the Dynamics of Bulk-Ensemble NMR Information Processing
• Reexamination of the evidence for entanglement in the D-Wave processor
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• Quantum Networks for Generating Arbitrary Quantum States
• The Promise of Quantum Simulation
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Cited by in corpus (20)

• Quantum Machine Learning
• Quantum machine learning: a classical perspective
• Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
• Quantum-assisted Helmholtz machines: A quantum-classical deep learning framework for industrial datasets in near-term devices
• Advances in silicon quantum photonics
• A Survey of Quantum Learning Theory
• Quantum Reinforcement Learning: the Maze problem
• Multiqubit and multilevel quantum reinforcement learning with quantum technologies
• Practical application improvement to Quantum SVM: theory to practice
• Quantum Enhanced Inference in Markov Logic Networks
• Measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti quantum computer
• Two new results about quantum exact learning
• A quantum algorithm for simulating non-sparse Hamiltonians
• Algorithmic quantum simulation of memory effects
• Quantum Machine Learning and its Supremacy in High Energy Physics
• Learning Simon's quantum algorithm
• Machine learning methods in quantum computing theory
• Generalization Study of Quantum Neural Network
• Quantum Machine Learning For Classical Data
• Quantum algorithmic differentiation