Series: De Gruyter Frontiers in Computational Intelligence, 6
Edited by: Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Sourav De, Elizabeth Behrman and Susanta Chakraborti
De Gruyter
2020
Series: De Gruyter Frontiers in Computational Intelligence, 6
Edited by: Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Sourav De, Elizabeth Behrman and Susanta Chakraborti
De Gruyter
2020
DOI:
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
Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Sourav De, Susanta Chakraborti, India.Elizabeth Behrman, USA.
MORE BY SIDDHARTHA BHATTACHARYYA
Editor of Predictive Intelligence in Biomedical and Health Informatics (2020)
Editor of Machine Learning Applications: Emerging Trends (2020)
Editor of Intelligent Decision Support Systems: Applications in Signal Processing (2019)
Editor of Big Data Security (2019)
MORE BY SOURAV DE
Contributor Of: Intelligent Multimedia Data Analysis (2019)
MORE BY INDRAJIT PAN
