| nGraph-HE2: A high-throughput framework for neural network inference on encrypted data F Boemer, A Costache, R Cammarota, C Wierzynski Proceedings of the 7th ACM workshop on encrypted computing & applied …, 2019 | 221 | 2019 |
| nGraph-HE: a graph compiler for deep learning on homomorphically encrypted data F Boemer, Y Lao, R Cammarota, C Wierzynski Proceedings of the 16th ACM international conference on computing frontiers …, 2019 | 167 | 2019 |
| MP2ML: A mixed-protocol machine learning framework for private inference F Boemer, R Cammarota, D Demmler, T Schneider, H Yalame Proceedings of the 15th international conference on availability …, 2020 | 130 | 2020 |
| Intel HEXL: accelerating homomorphic encryption with Intel AVX512-IFMA52 F Boemer, S Kim, G Seifu, F DM de Souza, V Gopal Proceedings of the 9th on Workshop on Encrypted Computing & Applied …, 2021 | 101* | 2021 |
| Parameter-free image segmentation with SLIC F Boemer, E Ratner, A Lendasse Neurocomputing 277, 228-236, 2018 | 41 | 2018 |
| Enabling homomorphically encrypted inference for large DNN models G Lloret-Talavera, M Jorda, H Servat, F Boemer, C Chauhan, ... IEEE Transactions on Computers 71 (5), 1145-1155, 2021 | 35 | 2021 |
| Accelerating encrypted computing on intel gpus Y Zhai, M Ibrahim, Y Qiu, F Boemer, Z Chen, A Titov, A Lyashevsky 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2022 | 28 | 2022 |
| Developing privacy-preserving AI systems: The lessons learned H Chen, SU Hussain, F Boemer, E Stapf, AR Sadeghi, F Koushanfar, ... 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-4, 2020 | 19 | 2020 |
| Trustworthy AI inference systems: An industry research view R Cammarota, M Schunter, A Rajan, F Boemer, Á Kiss, A Treiber, ... arXiv preprint arXiv:2008.04449, 2020 | 15 | 2020 |
| Systems, methods, apparatus and articles of manufacture to prevent unauthorized release of information associated with a function as a service R Cammarota, F Boemer, CM Wierzynski, A Rajan, R Misoczki US Patent App. 16/910,958, 2020 | 10 | 2020 |
| Processor with private pipeline C Wierzynski, F Boemer, R Cammarota US Patent 11,507,699, 2022 | 3 | 2022 |
| Conditional modular subtraction instruction F Boemer, V Gopal, G Seifu, S Kim, J Crawford US Patent App. 17/476,726, 2023 | 1 | 2023 |
| Privacy-Preserving Recommendation Generation FK Boemer, VK Chalasani, A Cherkashyn, ML Jockers, M Li, S Mohan, ... US Patent App. 18/437,866, 2024 | | 2024 |
| Private Retrieval of Location-Based Information R Rishi, FK Boemer, K Tarbe, BJ Van Ryswyk, M Zuliani, AAPS Bhowmick, ... US Patent App. 18/421,778, 2024 | | 2024 |
| Scalable Private Search with Wally H Asi, F Boemer, N Genise, MH Mughees, T Ogilvie, R Rishi, ... arXiv preprint arXiv:2406.06761, 2024 | | 2024 |
| Fused multiple multiplication and addition-subtraction instruction set F Boemer, V Gopal US Patent App. 17/695,554, 2023 | | 2023 |
| Multiple operation fused addition and subtraction instruction set F Boemer, V Gopal US Patent App. 17/695,533, 2023 | | 2023 |
| Apparatus and method for vector packed concatenate and shift of specific portions of quadwords F Boemer, V Gopal US Patent App. 17/560,554, 2023 | | 2023 |
| Zero extended 52-bit integer fused multiply add and subtract instructions F Boemer, V Gopal, G Seifu, S Kim, J Crawford US Patent App. 17/514,549, 2023 | | 2023 |
| Modular addition instruction F Boemer, V Gopal, G Seifu, S Kim, J Crawford US Patent App. 17/514,523, 2023 | | 2023 |
Rosario Cammarota ("Ro")Intel LabsZweryfikowany adres z ieee.org
