Eugenio Lomurno

According to our database, Eugenio Lomurno authored at least 22 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

POMONAG: Pareto-Optimal Many-Objective Neural Architecture Generator.

Eugenio Lomurno, Samuele Mariani, Matteo Monti, Matteo Matteucci

CoRR, 2024

FPBoost: Fully Parametric Gradient Boosting for Survival Analysis.

Alberto Archetti, Eugenio Lomurno, Diego Piccinotti, Matteo Matteucci

CoRR, 2024

Federated Knowledge Recycling: Privacy-Preserving Synthetic Data Sharing.

Eugenio Lomurno, Matteo Matteucci

CoRR, 2024

Synthetic Image Learning: Preserving Performance and Preventing Membership Inference Attacks.

Eugenio Lomurno, Matteo Matteucci

CoRR, 2024

A Lightweight Neural Architecture Search Model for Medical Image Classification.

Lunchen Xie, Eugenio Lomurno, Matteo Gambella, Danilo Ardagna, Manuel Roveri, Matteo Matteucci, Qingjiang Shi

CoRR, 2024

Stable Diffusion Dataset Generation for Downstream Classification Tasks.

Eugenio Lomurno, Matteo D'Oria, Matteo Matteucci

CoRR, 2024

Harnessing the Computing Continuum Across Personalized Healthcare, Maintenance and Inspection, and Farming 4.0.

Fatemeh Baghdadi, Davide Cirillo, Daniele Lezzi, Francesc Lordan, Fernando Vazquez, Eugenio Lomurno, Alberto Archetti, Danilo Ardagna, Matteo Matteucci

Proceedings of the 14th International Conference on Cloud Computing and Services Science, 2024

2023

POPNASv3: A pareto-optimal neural architecture search solution for image and time series classification.

Andrea Falanti, Eugenio Lomurno, Danilo Ardagna, Matteo Matteucci

Appl. Soft Comput., September, 2023

Age Group Discrimination via Free Handwriting Indicators.

Eugenio Lomurno, Simone Toffoli, Davide Di Febbo, Matteo Matteucci, Francesca Lunardini, Simona Ferrante

CoRR, 2023

Neural Architecture Transfer 2: A Paradigm for Improving Efficiency in Multi-Objective Neural Architecture Search.

Simone Sarti, Eugenio Lomurno, Matteo Matteucci

CoRR, 2023

Heterogeneous Datasets for Federated Survival Analysis Simulation.

Alberto Archetti, Eugenio Lomurno, Francesco Lattari, André Martin, Matteo Matteucci

Proceedings of the Companion of the 2023 ACM/SPEC International Conference on Performance Engineering, 2023

Two Steps Forward and One Behind: Rethinking Time Series Forecasting with Deep Learning.

Riccardo Ughi, Eugenio Lomurno, Matteo Matteucci

Proceedings of the Machine Learning, Optimization, and Data Science, 2023

Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits.

Simone Sarti, Eugenio Lomurno, Matteo Matteucci

Proceedings of the International Neural Network Society Workshop on Deep Learning Innovations and Applications, 2023

Enhancing Once-For-All: A Study on Parallel Blocks, Skip Connections and Early Exits.

Simone Sarti, Eugenio Lomurno, Andrea Falanti, Matteo Matteucci

Proceedings of the International Joint Conference on Neural Networks, 2023

Bridging the Gap: Enhancing the Utility of Synthetic Data via Post-Processing Techniques.

Eugenio Lomurno, Andrea Lampis, Matteo Matteucci

Proceedings of the 34th British Machine Vision Conference 2023, 2023

Discriminative Adversarial Privacy: Balancing Accuracy and Membership Privacy in Neural Networks.

Eugenio Lomurno, Alberto Archetti, Francesca Ausonio, Matteo Matteucci

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

On the Utility and Protection of Optimization with Differential Privacy and Classic Regularization Techniques.

Eugenio Lomurno, Matteo Matteucci

Proceedings of the Machine Learning, Optimization, and Data Science, 2022

POPNASv2: An Efficient Multi-Objective Neural Architecture Search Technique.

Andrea Falanti, Eugenio Lomurno, Stefano Samele, Danilo Ardagna, Matteo Matteucci

Proceedings of the International Joint Conference on Neural Networks, 2022

Improving Multi-View Stereo via Super-Resolution.

Eugenio Lomurno, Andrea Romanoni, Matteo Matteucci

Proceedings of the Image Analysis and Processing - ICIAP 2022, 2022

SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning.

Eugenio Lomurno, Alberto Archetti, Lorenzo Cazzella, Stefano Samele, Leonardo Di Perna, Matteo Matteucci

Proceedings of the 5th International Conference on Artificial Intelligence and Pattern Recognition, 2022

2021

A Generative Federated Learning Framework for Differential Privacy.

Eugenio Lomurno, Leonardo Di Perna, Lorenzo Cazzella, Stefano Samele, Matteo Matteucci

CoRR, 2021

Pareto-optimal progressive neural architecture search.

Eugenio Lomurno, Stefano Samele, Matteo Matteucci, Danilo Ardagna

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021