Results 41 to 50 of about 283,757 (265)
Quantum reinforcement learning [PDF]
Quantum Information Processing, 2023 AbstractIn this paper, we present implementations of an annealing-based and a gate-based quantum computing approach for finding the optimal policy to traverse a grid and compare them to a classical deep reinforcement learning approach. We extended these three approaches by allowing for stochastic actions instead of deterministic actions and by ...
Niels M. P. Neumann +2 more
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Quantum Adversarial Transfer Learning
Entropy, 2023 Adversarial transfer learning is a machine learning method that employs an adversarial training process to learn the datasets of different domains. Recently, this method has attracted attention because it can efficiently decouple the requirements of tasks from insufficient target data.
Longhan Wang, Yifan Sun, Xiangdong Zhang
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Federated Quantum Machine Learning
Entropy, 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 located.
Samuel Yen-Chi Chen, Shinjae Yoo
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PENGEMBANGAN ECONOMICS POCKET BOOK BERBASIS QUANTUM LEARNING UNTUK SISWA SEKOLAH MENENGAH ATAS
Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan, 2017 The purpose of this study is to produce and know the quality of quantum learning based economics pocket book. In developing economics pocket book the research uses design based research.
Ni Wayan Ayu Santi +2 more
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Frontiers in Physics, 2022 Multiclass classification is of great interest for various applications, for example, it is a common task in computer vision, where one needs to categorize an image into three or more classes.
Denis Bokhan +7 more
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Jurnal PAJAR (Pendidikan dan Pengajaran), 2022 Mathematics reflects students' reasoning and is determined by the use of learning models used by teachers. The research described in this article aims to describe the effectiveness of quantum learning models with Microsoft Kaizala on students’ learning ...
Ike Kuswardani, Nunuk Suryani, Yumiati
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Quantum adiabatic machine learning by zooming into a region of the energy surface [PDF]
, 2020 Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific application to Higgs boson classification.
Job, Joshua +5 more
core
Quantum Robot: Structure, Algorithms and Applications
, 2005 A kind of brand-new robot, quantum robot, is proposed through fusing quantum theory with robot technology. Quantum robot is essentially a complex quantum system and it is generally composed of three fundamental parts: MQCU (multi quantum computing units),
Chen, Chun-Lin +3 more
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A quantum speedup in machine learning: finding an N-bit Boolean function for a classification
New Journal of Physics, 2014 We compare quantum and classical machines designed for learning an N -bit Boolean function in order to address how a quantum system improves the machine learning behavior. The machines of the two types consist of the same number of operations and control
Seokwon Yoo +3 more
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Quantum learning algorithms for quantum measurements
, 2011 We study quantum learning algorithms for quantum measurements. The optimal learning algorithm is derived for arbitrary von Neumann measurements in the case of training with one or two examples.
Bisio, Alessandro +3 more
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