Results 31 to 40 of about 8,389,880 (297)
Machine Learning for Quantum Metrology [PDF]
11th Italian Quantum Information Science conference (IQIS2018), 2019 Phase estimation represents a significant example to test the application of quantum theory for enhanced measurements of unknown physical parameters. Several recipes have been developed, allowing to define strategies to reach the ultimate bounds in the asymptotic limit of a large number of trials. However, in certain applications it is crucial to reach
Spagnolo, Nicolò +5 more
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Energy Reports, 2022 Infrastructure development is expected to support economic growth in Indonesia. Infrastructure development related to logistics and energy is a top priority based on the Indonesia’s development plan.
Muhammad Arif Budiyanto +3 more
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Quantum computing and quantum machine learning classification – a survey
, 2022 The rapid development of machine learning technology leads to make the devices in the industries working autonomously. However, the growth of sensors in the industries leads to produce vast data that is utilized by machine learning algorithms to improve ...
Kuppusamy, P +7 more
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Discriminating Quantum States with Quantum Machine Learning [PDF]
2021 IEEE International Conference on Quantum Computing and Engineering (QCE), 2021 Quantum machine learning (QML) algorithms have obtained great relevance in the machine learning (ML) field due to the promise of quantum speedups when performing basic linear algebra subroutines (BLAS), a fundamental element in most ML algorithms. By making use of BLAS operations, we propose, implement and analyze a quantum k-means (qk-means) algorithm
David A. Quiroga +2 more
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IEEE Open Journal of Vehicular Technology, 2022 Quantum computing is envisaged as an evolving paradigm for solving computationally complex optimization problems with a large-number factorization and exhaustive search.
Trung Q. Duong +5 more
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Machine learning and quantum devices [PDF]
SciPost Physics Lecture Notes, 2021 These brief lecture notes cover the basics of neural networks and deep learning as well as their applications in the quantum domain, for physicists without prior knowledge. In the first part, we describe training using backpropagation, image classification, convolutional networks and autoencoders.
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, 2020 Click on the DOI link to access the article (may not be free).Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method.
De, Sourav +5 more
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Quantum Fair Machine Learning [PDF]
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 2021 In this paper, we inaugurate the field of quantum fair machine learning. We undertake a comparative analysis of differences and similarities between classical and quantum fair machine learning algorithms, specifying how the unique features of quantum computation alter measures, metrics and remediation strategies when quantum algorithms are subject to ...
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Quantum adiabatic machine learning [PDF]
Quantum Information Processing, 2012 21 pages, 9 ...
Kristen L. Pudenz, Daniel A. Lidar
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Quantum Machine Learning Implementations: Proposals and Experiments [PDF]
, 2023 This article gives an overview and a perspective of recent theoretical proposals and their experimental implementations in the field of quantum machine learning.
Lamata, Lucas, Lamata Manuel, Lucas
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