Quantum machine learning
Date
2020-06-08Author
Bhattacharyya, Siddhartha
Pan, Indrajit
Mani, Ashish
De, Sourav
Behrman, Elizabeth C.
Chakrabarti, Susanta
Metadata
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Bhattacharyya, S., Pan, I., Mani, A., De, S., Behrman, E., & Chakraborti, S. (Eds.). (2020). Quantum Machine Learning. Berlin, Boston: De Gruyter
Abstract
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. New trends in Machine Learning based on Quantum Computing and Quantum Algorithms Examples on real life applications Illustrative diagrams and coding examples.
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