| Privacy-preserving neural networks with Homomorphic encryption: Challenges and opportunities B Pulido-Gaytan, A Tchernykh, JM Cortés-Mendoza, M Babenko, ... Peer-to-Peer Networking and Applications 14 (3), 1666-1691, 2021 | 103 | 2021 |
| A survey on privacy-preserving machine learning with fully homomorphic encryption LB Pulido-Gaytan, A Tchernykh, JM Cortés-Mendoza, M Babenko, ... Latin American High Performance Computing Conference, 115-129, 2020 | 45 | 2020 |
| RRNS base extension error-correcting code for performance optimization of scalable reliable distributed cloud data storage M Babenko, A Tchernykh, B Pulido-Gaytan, JM Cortés-Mendoza, ... 2021 IEEE International Parallel and Distributed Processing Symposium …, 2021 | 14 | 2021 |
| Performance impact of error correction codes in RNS with returning methods and base extension E Shiryaev, E Bezuglova, M Babenko, A Tchernykh, B Pulido-Gaytan, ... 2021 International Conference Engineering and Telecommunication (En&T), 1-5, 2021 | 10 | 2021 |
| Privacy-preserving logistic regression as a cloud service based on residue number system JM Cortés-Mendoza, A Tchernykh, M Babenko, LB Pulido-Gaytán, ... Russian Supercomputing Days, 598-610, 2020 | 10 | 2020 |
| Towards the sign function best approximation for secure outsourced computations and control M Babenko, A Tchernykh, B Pulido-Gaytan, A Avetisyan, S Nesmachnow, ... Mathematics 10 (12), 2006, 2022 | 8 | 2022 |
| A Comparative Study of Secure Outsourced Matrix Multiplication Based on Homomorphic Encryption M Babenko, E Golimblevskaia, A Tchernykh, E Shiriaev, T Ermakova, ... Big Data and Cognitive Computing 7 (2), 84, 2023 | 7 | 2023 |
| LR-GD-RNS: enhanced privacy-preserving logistic regression algorithms for secure deployment in untrusted environments JM Cortés-Mendoza, G Radchenko, A Tchernykh, B Pulido-Gaytan, ... 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet …, 2021 | 7 | 2021 |
| Homomorphic comparison methods: Technologies, challenges, and opportunities M Babenko, A Tchernykh, E Golimblevskaia, LB Pulido-Gaytan, ... 2020 International Conference Engineering and Telecommunication (En&T), 1-5, 2020 | 7 | 2020 |
| Experimental evaluation of homomorphic comparison methods M Babenko, A Tchernykh, B Pulido-Gaytan, E Golimblevskaia, ... 2020 Ivannikov Ispras Open Conference (ISPRAS), 69-74, 2020 | 6 | 2020 |
| An efficient method for comparing numbers and determining the sign of a number in RNS for even ranges A Tchernykh, M Babenko, E Shiriaev, B Pulido-Gaytan, ... Computation 10 (2), 17, 2022 | 5 | 2022 |
| Toward digital twins' workload allocation on clouds with low-cost microservices streaming interaction A Tchernykh, A Facio-Medina, B Pulido-Gaytan, R Rivera-Rodriguez, ... 2020 Ivannikov Ispras Open Conference (ISPRAS), 115-121, 2020 | 5 | 2020 |
| Towards Understanding Efficient Privacy-Preserving Homomorphic Comparison B Pulido-Gaytan, A Tchernykh, F Leprévost, P Bouvry, A Goldman IEEE Access, 2023 | 4 | 2023 |
| Algorithm for constructing modular projections for correcting multiple errors based on a redundant residue number system using maximum likelihood decoding M Babenko, A Nazarov, A Tchernykh, B Pulido-Gaytan, ... Programming and Computer Software 47, 839-848, 2021 | 4 | 2021 |
| Multi-objective optimization of vehicle routing with environmental penalty LB Pulido-Gaytan, A Tchernykh, S Nesmachnow, A Cristóbal-Salas, ... Supercomputing: 10th International Conference on Supercomputing in Mexico …, 2019 | 4 | 2019 |
| Dynamic performance–Energy tradeoff consolidation with contention-aware resource provisioning in containerized clouds RM Canosa-Reyes, A Tchernykh, JM Cortés-Mendoza, B Pulido-Gaytan, ... Plos one 17 (1), e0261856, 2022 | 3 | 2022 |
| Improvement of the Approximate Method for the Comparison Operation in the RNS E Shiryaev, E Golimblevskaia, M Babenko, A Tchernykh, B Pulido-Gaytan 2020 International Conference Engineering and Telecommunication (En&T), 1-6, 2020 | 3 | 2020 |
| Optimization of Neural Network Training for Image Recognition Based on Trigonometric Polynomial Approximation N Vershkov, M Babenko, A Tchernykh, B Pulido-Gaytan, ... Programming and Computer Software 47, 830-838, 2021 | 2 | 2021 |
| Cryptographic Primitives Optimization Based on the Concepts of the Residue Number System and Finite Ring Neural Network A Tchernykh, M Babenko, B Pulido-Gaytan, E Shiryaev, E Golimblevskaia, ... International Conference on Optimization and Learning, 241-253, 2021 | 2 | 2021 |
| Self-learning activation functions to increase accuracy of privacy-preserving Convolutional Neural Networks with homomorphic encryption B Pulido-Gaytan, A Tchernykh Plos one 19 (7), e0306420, 2024 | | 2024 |
Andrei TchernykhProfessor of Computer Science, CICESE Research Center, MexicoVerified email at cicese.mx
