Sinem Sav

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 14

Top Topics

Top Venues

Proc. Priv. Enhancing Technol.

Publications

Halil Ibrahim Kanpak, Aqsa Shabbir, Esra Genç, Alptekin Küpçü, Sinem Sav
CURE: Privacy-Preserving Split Learning Done Right. CoRR (2024)
Natalija Mitic, Apostolos Pyrgelis, Sinem Sav
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study. CoRR (2024)
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)
Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux
Privacy-Preserving Federated Recurrent Neural Networks. Proc. Priv. Enhancing Technol. 2023 (4) (2023)
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 (2023)
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) (2022)
Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux
Privacy-Preserving Federated Recurrent Neural Networks. CoRR (2022)
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)
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) (2021)
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 (2020)
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 (2020)
Sinem Sav, David J. D. Hampson, Herbert H. Tsang
SIMARD: A simulated annealing based RNA design algorithm with quality pre-selection strategies. SSCI (2016)
Halid Emre Erhan, Sinem Sav, Stas Kalashnikov, Herbert H. Tsang
Examining the annealing schedules for RNA design algorithm. CEC (2016)
David J. D. Hampson, Sinem Sav, Herbert H. Tsang
Investigation of Multi-Objective Optimization criteria for RNA design. SSCI (2016)