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Global Optimum Search in Quantum Deep Learning
Lanston Hau Man Chu, Tejas Bhojraj, Rui Huang · 2020-08-09 · via cs.LG updates on arXiv.org

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 $O(\sqrt{|Θ|} N)$, but there is potential to improve PSTC further to $O(\sqrt{|Θ|} \cdot sublinear \ N)$ by enhancing the checking process.

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