Aug 30, 2021 · First, we will review a number of quantum classification algorithms, including quantum support vector machines, quantum kernel methods, quantum decision tree …

In this paper, we develop a novel classification algorithm that is based on the integration between competitive learning and the computational power of quantum computing. The proposed …

Nov 1, 2024 · In this study, we aim to highlight on two key aspects: (1) the classification of quantum machine learning algorithms, and (2) the thorough examination of challenges …

Feb 9, 2018 · In the emerging discipline of quantum machine learning, a number of quantum algorithms for classification have been proposed 2, 3, 4 and demonstrate how to train and use …

Jul 16, 2021 · Motivated by these developments, we present an embedding-based framework for supervised learning with trainable quantum circuits. We introduce both explicit and implicit …

Oct 19, 2022 · To manipulate multiple training samples with a higher expression ability, we propose a quantum algorithm for multi-class classification task in this paper. In the algorithm, …

Classification is a form of machine learning in which labels are assigned to data, often with respect to other data. For instance, we can classify between animals having 2 2 or 4 4 legs or …

Jul 14, 2022 · Based on the parameterized quantum circuit, we propose a hybrid quantum-classical convolutional neural network (HQCCNN) model for image classification that …

2 days ago · Additionally, the method incorporates optimization strategies from variational quantum algorithms (VQAs), enabling the quantum classifier to maintain high classification …

Jun 1, 2021 · Using a machine-learning algorithm, the team classifies data from a network of entangled sensors (Fig. 1). By comparing their scheme with one using classical data …