Local Binary and Multiclass SVMs Trained on a Quantum Annealer

arXiv:2403.08584v1 Announce Type: cross
Abstract: Support vector machines (SVMs) are widely used machine learning models (e.g., in remote sensing), with formulations for both classification and regression tasks. In the last years, with the advent of working quantum annealers, hybrid SVM models characterised by quantum training and classical execution have been introduced. These models have demonstrated comparable performance to their classical counterparts. However, they are limited in the training set size due to the restricted connectivity of the current quantum annealers. …

abstract arxiv binary classification cs.et cs.lg hybrid machine machine learning machine learning models machines quant-ph quantum regression sensing support support vector machines svm tasks training type vector