Quantum Computing Algorithms for Machine Learning and Signal Processing

This tutorial will present the basic concepts of quantum computing algorithms with the emphasis on Signal Processing and Machine Learning. The tutorial will start with the physics of quantum systems and cover basic concepts and properties including qubits, entanglement and qubit deciphering errors. We then begin focusing on quantum data and signal processing with details on the building blocks of computational operations, simulation, and implementation. The presenters will then discuss details of quantum computing and describe how to express quantum information processing algorithms. The discussion covers the methodologies used to transform classical machine learning algorithms to actual quantum expressions. The presentation on modeling algorithms will cover a hybrid classical-quantum approach and quantum simulators. In the last part of the tutorial, we present some of current industry and academic efforts,  available quantum toolkits and navigation through an extensive bibliography which we will also cover in our survey paper submitted to IISA 2021.

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