Quantum machine learning | Wikipedia audio article
Channel: wikipedia tts
Date: 24/12/2018

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Quantum_machine_learning


00:01:34 1 Machine learning with quantum computers
00:02:33 1.1 Linear algebra simulation with quantum amplitudes
00:04:54 1.2 Quantum machine learning algorithms based on Grover search
00:05:52 1.3 HHL Algorithm
00:06:20 1.4 Quantum-enhanced reinforcement learning
00:06:50 1.5 Quantum annealing
00:07:01 1.6 Quantum sampling techniques
00:07:45 1.7 Quantum neural networks
00:07:54 1.8 Hidden Quantum Markov Models
00:08:42 1.9 Fully quantum machine learning
00:12:53 2 Classical learning applied to quantum systems
00:14:46 2.1 Variational Circuits
00:16:07 3 Quantum learning theory
00:17:47 4 Implementations and experiments
00:19:55 5 See also
00:20:45 6 References
00:25:05 Implementations and experiments
00:28:57 See also



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SUMMARY
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Quantum machine learning is an emerging interdisciplinary research area at the intersection of quantum physics and machine learning. The most common use of the term refers to machine learning algorithms for the analysis of classical data executed on a quantum computer. While machine learning algorithms are used to compute immense quantities of data, quantum machine learning increases such capabilities intelligently, by creating opportunities to conduct analysis on quantum states and systems.This includes hybrid methods that involve both classical and quantum processing, where computationally difficult subroutines are outsourced to a quantum device. These routines can be more complex in nature and executed faster with the assistance of quantum devices. Furthermore, quantum algorithms can be used to analyze quantum states instead of classical data. Beyond quantum computing, the term "quantum machine learning" is often associated with machine learning methods applied to data generated from quantum experiments, such as learning quantum phase transitions or creating new quantum experiments. Quantum machine learning also extends to a branch of research that explores methodological and structural similarities between certain physical systems and learning systems, in particular neural networks. For example, some mathematical and numerical techniques from quantum physics are applicable to classical deep learning and vice versa. Finally, researchers investigate more abstract notions of learning theory with respect to quantum information, sometimes referred to as "quantum learning theory".