量子机器学习金融ICCAD特别会议论文

Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts, Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen, Pradeep Niroula, Arthur G. Rattew, Yue Sun, Romina Yalovetzky
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引用次数: 16

摘要

量子计算机有望在这十年内超越经典计算机的计算能力,并对许多行业,特别是金融领域产生颠覆性影响。事实上,金融预计将是第一个受益于量子计算的行业,不仅在中长期,甚至在短期内都是如此。这篇综述文章介绍了量子算法在金融应用中的最新进展,特别关注那些可以通过机器学习解决的用例。
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Quantum Machine Learning for Finance ICCAD Special Session Paper
Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, particularly finance. In fact, finance is estimated to be the first industry sector to benefit from Quantum Computing not only in the medium and long terms, but even in the short term. This review paper presents the state of the art of quantum algorithms for financial applications, with particular focus to those use cases that can be solved via Machine Learning.
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