Fabian Boemer

According to our database, Fabian Boemer authored at least 10 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Enabling Homomorphically Encrypted Inference for Large DNN Models.

Guillermo Lloret-Talavera, Marc Jordà, Harald Servat, Fabian Boemer, Chetan Chauhan, Shigeki Tomishima, Nilesh N. Shah, Antonio J. Peña

IEEE Trans. Computers, 2022

Accelerating Encrypted Computing on Intel GPUs.

Yujia Zhai, Mohannad Ibrahim, Yiqin Qiu, Fabian Boemer, Zizhong Chen, Alexey Titov, Alexander Lyashevsky

Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

2021

Intel HEXL: Accelerating Homomorphic Encryption with Intel AVX512-IFMA52.

Fabian Boemer, Sejun Kim, Gelila Seifu, Fillipe D. M. de Souza, Vinodh Gopal

IACR Cryptol. ePrint Arch., 2021

2020

MP2ML: A Mixed-Protocol Machine Learning Framework for Private Inference.

Fabian Boemer, Rosario Cammarota, Daniel Demmler, Thomas Schneider, Hossein Yalame

IACR Cryptol. ePrint Arch., 2020

Trustworthy AI Inference Systems: An Industry Research View.

Rosario Cammarota, Matthias Schunter, Anand Rajan, Fabian Boemer, Ágnes Kiss, Amos Treiber, Christian Weinert, Thomas Schneider, Emmanuel Stapf, Ahmad-Reza Sadeghi, Daniel Demmler, Huili Chen, Siam Umar Hussain, M. Sadegh Riazi, Farinaz Koushanfar, Saransh Gupta, Tajana Simunic Rosing, Kamalika Chaudhuri, Hamid Nejatollahi, Nikil D. Dutt, Mohsen Imani, Kim Laine, Anuj Dubey, Aydin Aysu, Fateme Sadat Hosseini, Chengmo Yang, Eric Wallace, Pamela Norton

CoRR, 2020

Developing Privacy-preserving AI Systems: The Lessons learned.

Huili Chen, Siam Umar Hussain, Fabian Boemer, Emmanuel Stapf, Ahmad-Reza Sadeghi, Farinaz Koushanfar, Rosario Cammarota

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019

nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data.

Fabian Boemer, Yixing Lao, Rosario Cammarota, Casimir Wierzynski

IACR Cryptol. ePrint Arch., 2019

nGraph-HE2: A High-Throughput Framework for Neural Network Inference on Encrypted Data.

Fabian Boemer, Anamaria Costache, Rosario Cammarota, Casimir Wierzynski

IACR Cryptol. ePrint Arch., 2019

2018

Parameter-free image segmentation with SLIC.

Fabian Boemer, Edward R. Ratner, Amaury Lendasse

Neurocomputing, 2018

nGraph-HE: A Graph Compiler for Deep Learning on Homomorphically Encrypted Data.

Fabian Boemer, Yixing Lao, Casimir Wierzynski

CoRR, 2018