| 书目名称 | Supervised Learning with Quantum Computers |
| 编辑 | Maria Schuld,Francesco Petruccione |
| 视频video | |
| 概述 | Explains relevant concepts and terminology from machine learning and quantum information in an accessible language.Introduces a structure into the literature by clustering the work in terms of what as |
| 丛书名称 | Quantum Science and Technology |
| 图书封面 |  |
| 描述 | .Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models‘‘. A special focus lies on supervised learning, and applications for near-term quantum devices.. |
| 出版日期 | Book 2018 |
| 关键词 | quantum phase estimation; quantum walks; quantum annealing; hidden Markov models; belief nets; Boltzmann |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-96424-9 |
| isbn_softcover | 978-3-030-07188-2 |
| isbn_ebook | 978-3-319-96424-9Series ISSN 2364-9054 Series E-ISSN 2364-9062 |
| issn_series | 2364-9054 |
| copyright | Springer Nature Switzerland AG 2018 |
发表于 2025-3-21 17:43:12
