On the utility and protection of optimization with differential privacy
and classic regularization techniques

On the utility and protection of optimization with differential privacy and classic regularization techniques

7 September 2022

Eugenio Lomurno

Matteo matteucci

Papers citing "On the utility and protection of optimization with differential privacy and classic regularization techniques"

9 / 9 papers shown

Title
Spectral and Temporal Denoising for Differentially Private Optimization Hyeju Shin Kyudan Jung Seongwon Yun Juyoung Yun 33 0 0 07 May 2025
Your Image Generator Is Your New Private Dataset Nicolo Resmini Eugenio Lomurno Cristian Sbrolli Matteo Matteucci 26 0 0 06 Apr 2025
Differential Privacy Regularization: Protecting Training Data Through Loss Function Regularization Francisco Aguilera-Martínez Fernando Berzal 35 0 0 25 Sep 2024
Federated Knowledge Recycling: Privacy-Preserving Synthetic Data Sharing Eugenio Lomurno Matteo Matteucci 36 2 0 30 Jul 2024
Synthetic Image Learning: Preserving Performance and Preventing Membership Inference Attacks Eugenio Lomurno Matteo Matteucci MedIm 36 3 0 22 Jul 2024
Harnessing the Computing Continuum across Personalized Healthcare, Maintenance and Inspection, and Farming 4.0 Fatemeh Baghdadi Davide Cirillo D. Lezzi Francesc Lordan Fernando Vazquez Eugenio Lomurno Alberto Archetti Danilo Ardagna Matteo Matteucci 33 1 0 23 Feb 2024
DISTINQT: A Distributed Privacy Aware Learning Framework for QoS Prediction for Future Mobile and Wireless Networks Nikolaos Koursioumpas Lina Magoula Ioannis Stavrakakis Nancy Alonistioti M. A. Gutierrez-Estevez R. Khalili 17 1 0 15 Jan 2024
Discriminative Adversarial Privacy: Balancing Accuracy and Membership Privacy in Neural Networks Eugenio Lomurno Alberto Archetti Francesca Ausonio Matteo Matteucci AAML 17 4 0 05 Jun 2023
To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout Prateek Jain Vivek Kulkarni Abhradeep Thakurta Oliver Williams 34 30 0 06 Mar 2015