Quantum Machine Learning

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system.
While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices.

About the author

Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Sourav De, Susanta Chakraborti, India. Elizabeth Behrman, USA.

Product details

• Assisted by: Elizabeth Behrman (Editor), Siddhartha Bhattacharyya (Editor), Susanta Chakraborti (Editor), Sourav De (Editor), Ashish Mani (Editor), Ashish Mani et al (Editor), Indrajit Pan (Editor)
• Publisher: De Gruyter
• Languages: English
• Product format: Hardback
• Released: 01.01.2020
• EAN: 9783110670646
• ISBN: 978-3-11-067064-6
• No. of pages: 118
• Dimensions: 175 mm x 13 mm x 246 mm
• Weight: 356 g
• Illustrations: 6 b/w ill., 6 b/w tbl.
• Series: De Gruyter Frontiers in Computational Intelligence
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT