3 papers
quant-ph2025
Embedding-Aware Quantum-Classical SVMs for Scalable Quantum Machine Learning
Sebastián Andrés Cajas Ordóñez, Luis Fernando Torres Torres, Mario Bifulco +3
Quantum Support Vector Machines face scalability challenges due to high-dimensional quantum states and hardware limitations. We propose an embedding-aware quantum-classical pipelin…
quant-ph2025
Exploring Topologies in Quantum Annealing: A Hardware-Aware Perspective
Mario Bifulco, Luca Roversi
Quantum Annealing (QA) offers a promising framework for solving NP-hard optimization problems, but its effectiveness is constrained by the topology of the underlying quantum hardwa…
quant-ph2025
Exploring an implementation of quantum learning pipeline for support vector machines
Mario Bifulco, Luca Roversi
This work presents a fully quantum approach to support vector machine (SVM) learning by integrating gate-based quantum kernel methods with quantum annealing-based optimization. We…