Results 11 to 20 of about 8,042,432 (193)
Federated Quantum Machine Learning. [PDF]
Entropy (Basel), 2021 Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is ...
Chen SY, Yoo S.
europepmc +8 more sources
Quantum adversarial machine learning [PDF]
Physical Review Research, 2020 Adversarial machine learning is an emerging field that focuses on studying vulnerabilities of machine learning approaches in adversarial settings and developing techniques accordingly to make learning robust to adversarial manipulations. It plays a vital
Sirui Lu, Lu-Ming Duan, Dong-Ling Deng
doaj +4 more sources
Quantum machine learning and quantum biomimetics: A perspective
Machine Learning: Science and Technology, 2020 Quantum machine learning has emerged as an exciting and promising paradigm inside quantum technologies. It may permit, on the one hand, to carry out more efficient machine learning calculations by means of quantum devices, while, on the other hand, to ...
Lamata Manuel, Lucas
core +6 more sources
Quantum machine learning in ophthalmology. [PDF]
Eye (Lond)Masalkhi M, Ong J, Waisberg E, Lee AG.
europepmc +3 more sources
Quantum Reinforcement Learning with Quantum Photonics
Photonics, 2021 Quantum machine learning has emerged as a promising paradigm that could accelerate machine learning calculations. Inside this field, quantum reinforcement learning aims at designing and building quantum agents that may exchange information with their ...
Lucas Lamata
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Quantum-Enhanced Machine Learning [PDF]
Physical Review Letters, 2016 5+15 pages. This paper builds upon and mostly supersedes arXiv:1507.08482. In addition to results provided in this previous work, here we achieve learning improvements in more general environments, and provide connections to other work in quantum machine learning. Explicit constructions of oracularized environments given in arXiv:1507.08482 are omitted
Vedran Dunjko +2 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 ...
openaire +2 more sources
Quantum Machine Learning Applications in the Biomedical Domain: A Systematic Review
IEEE Access, 2022 Quantum technologies have become powerful tools for a wide range of application disciplines, which tend to range from chemistry to agriculture, natural language processing, and healthcare due to exponentially growing computational power and advancement ...
Danyal Maheshwari +2 more
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Quantum Machine Learning with SQUID
Quantum, 2022 In this work we present the Scaled QUantum IDentifier (SQUID), an open-source framework for exploring hybrid Quantum-Classical algorithms for classification problems. The classical infrastructure is based on PyTorch and we provide a standardized design to implement a variety of quantum models with the capability of back-propagation for efficient ...
Roggero, Alessandro +3 more
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Machine learning aided carrier recovery in continuous-variable quantum key distribution
npj Quantum Information, 2021 The secret key rate of a continuous-variable quantum key distribution (CV-QKD) system is limited by excess noise. A key issue typical to all modern CV-QKD systems implemented with a reference or pilot signal and an independent local oscillator is ...
Hou-Man Chin +4 more
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