量子深度学习(quantum deep learning) 主要是指量子玻尔兹曼机(quantum Boltzmann Machine). 类似于经典的玻尔兹曼机,量子玻尔兹曼机的训练也是寻找一系列参数,来找到可以使得input training data近似满足玻尔兹曼分布(即统计物理里面的thermal分布)。量子算法相比经典算法的优势在于,更好的采样,更快的thermalize过程亦即更快的...
Supervised learningis an ML paradigm that learns or trains a function that maps the input to output given the input-output pairs26. That is, given the training dataset\(\{({\varvec{x_i}},{\varvec{y_i}})\}\), it is expected that after successful training, the learned function\(f_...
Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML ...
(https://www.dwavesys.com/tutorials/background-reading-series/quantum-computing-primer) Why Quantum Machine Learning? Machine Learning(ML) is just a term in recent days but the work effort start from 18th century. What is Machine Learning ? , In Simple word the answer is making the computer...
·教育与培训(Education and Training):加强对量子计算的教育和培训,培养更多的技术人才和专业人士。 结论:量子计算的未来愿景 Conclusion: The Future Vision of Quantum Computing 量子计算作为一种前沿技术,将在科学、技术和社会领域带来深远的影响。尽管面临诸多挑战,但其巨大的潜力和应用前景使其成为未来科技发展的重...
Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum ...
(i.e. mean coordinates of each group in the training data) closest to the point being classified. In addition to finding the Nearest Centroid,fit_and_predictalso currently supports quantum versions of k-Nearest Neighbors (regressor and classifier) as well as k-means for unsupervised lear...
·教育与培训(Education and Training):加强对量子计算的教育和培训,培养更多的技术人才和专业人士。 结论:量子计算的未来愿景 Conclusion: The Future Vision of Quantum Computing 量子计算作为一种前沿技术,将在多个领域带来深远的变革。尽管面临技术挑战和商业化障碍,但其巨大的潜力和广泛的应用前景使得量子计算成为未...
Benchmarking quantum machine learning kernel training for classification tasks Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine... Alvarez-Estevez, Diego 被引量: 0发表: 2024年 Reinforcement learning...
Exploiting quantum superposition, quantum machine learning provides the hope for resolving difficulties in big data and training process, and new learning models illuminated by quantum physics. So far, the field is still in its infancy.Although many problems had been explored, a systematic theory is...