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Moran Baruch
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2020 – today
- 2023
- [j1]Ehud Aharoni
, Allon Adir, Moran Baruch, Nir Drucker
, Gilad Ezov, Ariel Farkash, Lev Greenberg, Ramy Masalha, Guy Moshkowich, Dov Murik, Hayim Shaul, Omri Soceanu:
HeLayers: A Tile Tensors Framework for Large Neural Networks on Encrypted Data. Proc. Priv. Enhancing Technol. 2023(1): 325-342 (2023) - [c3]Ehud Aharoni, Moran Baruch, Pradip Bose, Alper Buyuktosunoglu, Nir Drucker, Subhankar Pal, Tomer Pelleg, Kanthi K. Sarpatwar, Hayim Shaul, Omri Soceanu, Roman Vaculín:
Efficient Pruning for Machine Learning Under Homomorphic Encryption. ESORICS (4) 2023: 204-225 - [i7]Moran Baruch, Nir Drucker, Gilad Ezov, Eyal Kushnir, Jenny Lerner, Omri Soceanu, Itamar Zimerman:
Sensitive Tuning of Large Scale CNNs for E2E Secure Prediction using Homomorphic Encryption. CoRR abs/2304.14836 (2023) - [i6]Itamar Zimerman, Moran Baruch, Nir Drucker, Gilad Ezov, Omri Soceanu, Lior Wolf:
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption. CoRR abs/2311.08610 (2023) - 2022
- [c2]Moran Baruch
, Nir Drucker
, Lev Greenberg
, Guy Moshkowich
:
A Methodology for Training Homomorphic Encryption Friendly Neural Networks. ACNS Workshops 2022: 536-553 - [i5]Ehud Aharoni, Moran Baruch, Pradip Bose, Alper Buyuktosunoglu, Nir Drucker, Subhankar Pal, Tomer Pelleg, Kanthi K. Sarpatwar, Hayim Shaul, Omri Soceanu, Roman Vaculín:
HE-PEx: Efficient Machine Learning under Homomorphic Encryption using Pruning, Permutation and Expansion. CoRR abs/2207.03384 (2022) - 2021
- [i4]Moran Baruch, Lev Greenberg, Guy Moshkowich:
Fighting COVID-19 in the Dark: Methodology for Improved Inference Using Homomorphically Encrypted DNN. CoRR abs/2111.03362 (2021) - 2020
- [i3]Ehud Aharoni, Allon Adir, Moran Baruch, Gilad Ezov, Ariel Farkash, Lev Greenberg, Ramy Masalha, Dov Murik, Omri Soceanu:
Tile Tensors: A versatile data structure with descriptive shapes for homomorphic encryption. CoRR abs/2011.01805 (2020)
2010 – 2019
- 2019
- [c1]Gilad Baruch, Moran Baruch, Yoav Goldberg:
A Little Is Enough: Circumventing Defenses For Distributed Learning. NeurIPS 2019: 8632-8642 - [i2]Moran Baruch, Gilad Baruch, Yoav Goldberg:
A Little Is Enough: Circumventing Defenses For Distributed Learning. CoRR abs/1902.06156 (2019) - 2018
- [i1]Felix Kreuk, Assi Barak, Shir Aviv-Reuven, Moran Baruch, Benny Pinkas, Joseph Keshet:
Adversarial Examples on Discrete Sequences for Beating Whole-Binary Malware Detection. CoRR abs/1802.04528 (2018)
Coauthor Index
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