QUANTUM-BASED EXTREME LEARNING MACHINE

A quantum-based extreme learning machine and a method for training a quantum-based extreme learning machine using a quantum processor (50) implementing a quantum substrate (220) and a set of training data (260) is disclosed. The training data comprises input features vectors (400) with a plurality of N parameters (262) and true labels vector (265). The method comprises uploading (S610) the training data (260) to the quantum processor (50), encoding (S620) the uploaded training data (260), passing (S410, S630) a plurality of subsets of the input features vector (400) from the training data (260) through the quantum substrate (220) to obtain a plurality of output vectors of expectation values (420), concatenation (S420) of the plurality of output vectors of expectation values (420) to construct (S430) a matrix (430), computation (S440) of an inverse matrix (H) from the matrix (430) and multiplication (S450) of the inverse matrix (H) by the true labels vector (265) to obtain a vector (470) of optimal weights β.