Quantum Machine Learning / / ed. by Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Elizabeth Behrman, Susanta Chakraborti, Sourav De.

• Superior document: Title is part of eBook package: De Gruyter DG Ebook Package English 2020
• HerausgeberIn: Behrman, Elizabeth,; Bhattacharyya, Siddhartha,; Chakraborti, Susanta,; De, Sourav,; Mani, Ashish,; Pan, Indrajit,
• MitwirkendeR: Bhattacharyya, Siddhartha,; Bishwas, Arit Kumar,; Chatterjee, Amlan,; De, Sourav,; Dey, Alokananda,; Dey, Sandip,; MacLennan, Bruce J.,; Mani, Ashish,; Palade, Vasile,; Platos, Jan,
• Place / Publishing House: Berlin ;, Boston : : De Gruyter, , [2020]; ©2020
• Year of Publication: 2020
• Language: English
• Series: De Gruyter Frontiers in Computational Intelligence , 6
• Physical Description: 1 online resource (XIII, 118 p.)

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 inf...

Table of Contents

• Frontmatter
• Contents
• List of Contributors
• Preface
• 1. Introduction to quantum machine learning
• 2. Topographic representation for quantum machine learning
• 3. Quantum optimization for machine learning
• 4. From classical to quantum machine learning
• 5. Quantum inspired automatic clustering algorithms: A comparative study of Genetic algorithm and Bat algorithm
• 6. Conclusion
• Index