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Quantum-Computing-Inspired Algorithms in Machine Learning

Quantum-Computing-Inspired Algorithms in Machine Learning
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Author(s): Deeksha Kaul (VIT University, India), Harika Raju (VIT University, India)and B. K. Tripathy (VIT University, India)
Copyright: 2018
Pages: 26
Source title: Quantum-Inspired Intelligent Systems for Multimedia Data Analysis
Source Author(s)/Editor(s): Siddhartha Bhattacharyya (RCC Institute of Information Technology, India)
DOI: 10.4018/978-1-5225-5219-2.ch001

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Abstract

In this chapter, the authors discuss the use of quantum computing concepts to optimize the decision-making capability of classical machine learning algorithms. Machine learning, a subfield of artificial intelligence, implements various techniques to train a computer to learn and adapt to various real-time tasks. With the volume of data exponentially increasing, solving the same problems using classical algorithms becomes more tedious and time consuming. Quantum computing has varied applications in many areas of computer science. One such area which has been transformed a lot through the introduction of quantum computing is machine learning. Quantum computing, with its ability to perform tasks in logarithmic time, aids in overcoming the limitations of classical machine learning algorithms.

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