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Sinem Sav
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2020 – today
- 2025
- [c6]Santhosh Parampottupadam, Ralf Floca, Dimitrios Bounias, Benjamin Hamm, Saikat Roy, Sinem Sav, Maximilian Zenk, Klaus H. Maier-Hein
:
Abstract: Client Security Alone Fails in Federated Learning - 2D and 3D Attack Insights. Bildverarbeitung für die Medizin 2025: 283 - 2024
- [i7]Natalija Mitic, Apostolos Pyrgelis, Sinem Sav:
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study. CoRR abs/2402.16087 (2024) - [i6]Halil Ibrahim Kanpak, Aqsa Shabbir, Esra Genç, Alptekin Küpçü, Sinem Sav:
CURE: Privacy-Preserving Split Learning Done Right. CoRR abs/2407.08977 (2024) - [i5]Atilla Akkus, Mingjie Li, Junjie Chu, Michael Backes, Yang Zhang, Sinem Sav:
Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data. CoRR abs/2409.11423 (2024) - 2023
- [j3]Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Privacy-Preserving Federated Recurrent Neural Networks. Proc. Priv. Enhancing Technol. 2023(4): 500-521 (2023) - [c5]Francesco Intoci, Sinem Sav, Apostolos Pyrgelis, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference. ACNS Workshops 2023: 359-377 - [i4]Francesco Intoci, Sinem Sav, Apostolos Pyrgelis, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference. CoRR abs/2305.00690 (2023) - 2022
- [j2]Sinem Sav, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Manfred Claassen, Jean-Pierre Hubaux:
Privacy-preserving federated neural network learning for disease-associated cell classification. Patterns 3(5): 100487 (2022) - [i3]Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Privacy-Preserving Federated Recurrent Neural Networks. CoRR abs/2207.13947 (2022) - 2021
- [j1]David Froelicher, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav
, Joao Sa Sousa, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Scalable Privacy-Preserving Distributed Learning. Proc. Priv. Enhancing Technol. 2021(2): 323-347 (2021) - [c4]Sinem Sav, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux:
POSEIDON: Privacy-Preserving Federated Neural Network Learning. NDSS 2021 - 2020
- [i2]David Froelicher, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav, Joao Sa Sousa, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Scalable Privacy-Preserving Distributed Learning. CoRR abs/2005.09532 (2020) - [i1]Sinem Sav, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux:
POSEIDON: Privacy-Preserving Federated Neural Network Learning. CoRR abs/2009.00349 (2020)
2010 – 2019
- 2016
- [c3]Halid Emre Erhan, Sinem Sav, Stas Kalashnikov, Herbert H. Tsang
:
Examining the annealing schedules for RNA design algorithm. CEC 2016: 1295-1302 - [c2]David J. D. Hampson, Sinem Sav, Herbert H. Tsang
:
Investigation of Multi-Objective Optimization criteria for RNA design. SSCI 2016: 1-8 - [c1]Sinem Sav, David J. D. Hampson, Herbert H. Tsang
:
SIMARD: A simulated annealing based RNA design algorithm with quality pre-selection strategies. SSCI 2016: 1-8
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last updated on 2025-03-10 21:55 CET by the dblp team
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