1 citations · 1 across the 4 of their papers we have counts for
4 papers
Enhancement of Quantum Semi-Supervised Learning via Improved Laplacian and Poisson Methods
Hamed Gholipour, Farid Bozorgnia, Hamzeh Mohammadigheymasi +5
This paper develops a hybrid quantum approach for graph-based semi-supervised learning to enhance performance in scenarios where labeled data is scarce. We introduce two enhanced q…
Graph-Based Semi-Supervised Segregated Lipschitz Learning
Farid Bozorgnia, Yassine Belkheiri, Abderrahim Elmoataz
This paper presents an approach to semi-supervised learning for the classification of data using the Lipschitz Learning on graphs. We develop a graph-based semi-supervised learning…
A Laplacian-based Quantum Graph Neural Network for Semi-Supervised Learning
Hamed Gholipour, Farid Bozorgnia, Kailash Hambarde +5
Laplacian learning method is a well-established technique in classical graph-based semi-supervised learning, but its potential in the quantum domain remains largely unexplored. Thi…
Improved Graph-based semi-supervised learning Schemes
Farid Bozorgnia
In this work, we improve the accuracy of several known algorithms to address the classification of large datasets when few labels are available. Our framework lies in the realm of…