MicroAlgo announces quantum entanglement-based novel training algorithm

MicroAlgo (MLGO) announced the development of a novel quantum entanglement-based training algorithm – the Entanglement-Assisted Training Algorithm for Supervised Quantum Classifiers. They also introduced a cost function based on Bell inequalities, enabling the simultaneous encoding of errors from multiple training samples. This breakthrough surpasses the capability limits of traditional algorithms, offering an efficient and widely applicable solution for supervised quantum classifiers. The core of MicroAlgo’s entanglement-assisted training algorithm for supervised quantum classifiers lies in leveraging quantum entanglement to construct a model capable of simultaneously operating on multiple training samples and their corresponding labels.