4 papers
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…
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…
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…
Quantum-Classical Sentiment Analysis
Mario Bifulco, Luca Roversi
In this study, we initially investigate the application of a hybrid classical-quantum classifier (HCQC) for sentiment analysis, comparing its performance against the classical CPLE…