Global Optimum Search in Quantum Deep Learning
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This paper aims to solve machine learning optimization problem by using quantum circuit. Two approaches, namely the average approach and the Partial Swap Test Cut-off method (PSTC) was proposed to search for the global minimum/maximum of two different objective functions. The current cost is O(√(|Θ|) N), but there is potential to improve PSTC further to O(√(|Θ|)· sublinear N) by enhancing the checking process.
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