Exploiting unintended feature leakage in collaborative learning L Melis, C Song, E De Cristofaro, V Shmatikov
2019 IEEE symposium on security and privacy (SP), 691-706, 2019
2045 2019 Logan: Membership inference attacks against generative models J Hayes, L Melis, G Danezis, E De Cristofaro
arXiv preprint arXiv:1705.07663, 2017
755 * 2017 Differentially private mixture of generative neural networks G Acs, L Melis, C Castelluccia, E De Cristofaro
IEEE Transactions on Knowledge and Data Engineering 31 (6), 1109-1121, 2018
181 2018 Efficient private statistics with succinct sketches L Melis, G Danezis, E De Cristofaro
NDSS 2016, 2015
164 2015 Differentially private query release through adaptive projection S Aydore, W Brown, M Kearns, K Kenthapadi, L Melis, A Roth, AA Siva
International Conference on Machine Learning, 457-467, 2021
89 2021 Splitbox: Toward efficient private network function virtualization HJ Asghar, L Melis, C Soldani, E De Cristofaro, MA Kaafar, L Mathy
Proceedings of the 2016 workshop on Hot topics in Middleboxes and Network …, 2016
54 2016 Private processing of outsourced network functions: Feasibility and constructions L Melis, HJ Asghar, E De Cristofaro, MA Kaafar
Proceedings of the 2016 ACM International Workshop on Security in Software …, 2016
40 2016 Adversarial robustness with non-uniform perturbations E Erdemir, J Bickford, L Melis, S Aydore
Advances in Neural Information Processing Systems 34, 19147-19159, 2021
34 2021 Towards fair federated recommendation learning: Characterizing the inter-dependence of system and data heterogeneity K Maeng, H Lu, L Melis, J Nguyen, M Rabbat, CJ Wu
Proceedings of the 16th ACM Conference on Recommender Systems, 156-167, 2022
33 2022 Have Missing Data? Make It Miss More! Imputing Tabular Data with Masked Autoencoding T Du, L Melis, T Wang
17 * Federated linear contextual bandits with user-level differential privacy R Huang, H Zhang, L Melis, M Shen, M Hejazinia, J Yang
International Conference on Machine Learning, 14060-14095, 2023
16 2023 Detecting anomalous events using autoencoders B Coskun, W Ding, L Melis
US Patent 11,374,952, 2022
15 2022 Measuring and Privately Building Highly Predictive Blacklisting L Melis, A Pyrgelis, E De Cristofaro
15 * Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems. M Hejazinia, D Huba, I Leontiadis, K Maeng, M Malek, L Melis, I Mironov, ...
IEEE Data Eng. Bull. 46 (1), 145-157, 2023
9 * 2023 Noisy Neighbors: Efficient membership inference attacks against LLMs F Galli, L Melis, T Cucinotta
arXiv preprint arXiv:2406.16565, 2024
6 2024 EXACT: Extensive Attack for Split Learning X Qiu, I Leontiadis, L Melis, A Sablayrolles, P Stock
arXiv preprint arXiv:2305.12997, 2023
6 * 2023 Detecting anomalous events from categorical data using autoencoders S Aydore, B Coskun, L Melis
US Patent 11,537,902, 2022
6 2022 Auditing S Mahloujifar, L Melis, K Chaudhuri
arXiv preprint arXiv:2410.22235, 2024
2 2024 Building and evaluating privacy-preserving data processing systems L Melis
UCL (University College London), 2018
2 2018 Fast privacy-preserving network function outsourcing HJ Asghar, E De Cristofaro, G Jourjon, MA Kaafar, L Mathy, L Melis, ...
Computer Networks 163, 106893, 2019
1 2019 
Emiliano De CristofaroProfessor at University of California, RiversideBestätigte E-Mail-Adresse bei ucr.edu