AutoQML: Automatic Generation and Training of Robust Quantum-Inspired Classifiers by Using Genetic Algorithms on Grayscale Images. (arXiv:2208.13246v1 [quant-ph])

We propose a new hybrid system for automatically generating and training
quantum-inspired classifiers on grayscale images by using multiobjective
genetic algorithms. We define a dynamic fitness function to obtain the smallest
possible circuit and highest accuracy on unseen data, ensuring that the
proposed technique is generalizable and robust. We minimize the complexity of
the generated circuits in terms of the number of entanglement gates by
penalizing their appearance. We reduce the size of the images with two
dimensionality reduction approaches: …

algorithms arxiv classifiers generation images quantum training