Emerging Computing Paradigms

5 Quantum Machine Learning Algorithms

Renata Wong¹, Tanya Garg², Ritu Thombre³, Alberto Maldonado Romo⁴, Niranjan PN⁵, Pinaki Sen⁶, Mandeep Kaur Saggi⁷ and Amandeep Singh Bhatia⁸

¹Physics Division, National Center for Theoretical Sciences, Taipei, Taiwan ROC

²Indian Institute of Technology, Roorkee, Uttarakhand, India

³Computer Science and Engineering Department, Visvesvaraya National Institute of Technology, Nagpur, India

⁴Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City, Mexico

⁵Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India

⁶National Institute of Technology, Agartala, Tripura, India

⁷Computer Science and Engineering Department, Thapar Institute of Engineering & Technology, Patiala, Punjab, India

⁸School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

5.1 Introduction

The artificial intelligence and machine learning are important tools for solving real-world problems and have got significant attention among scientific research community, business and industry. In the past decade, machine learning traversed a vast array of algorithms ranging from speech recognition, self-driving cars, web searching effectively, and enormously improved the realization of the human genome. The machine learning algorithms learn by an interplay and upgrade automatically via experience using data [1, 2]. The algorithms are divided into mainly three categories i.e., supervised learning for task-driven tasks, unsupervised ...