| Federated learning with local differential privacy: Trade-offs between privacy, utility, and communication M Kim, O Günlü, RF Schaefer ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 98 | 2021 |
| Coded matrix multiplication on a group-based model M Kim, J Sohn, J Moon 2019 IEEE International Symposium on Information Theory (ISIT), 722-726, 2019 | 29 | 2019 |
| Learning End-to-End Channel Coding with Diffusion Models M Kim, R Fritschek, RF Schaefer WSA & SCC 2023; 26th International ITG Workshop on Smart Antennas and 13th …, 2023 | 10 | 2023 |
| Randomized nested polar subcode constructions for privacy, secrecy, and storage O Günlü, P Trifonov, M Kim, RF Schaefer, V Sidorenko 2020 International Symposium on Information Theory and Its Applications …, 2020 | 10 | 2020 |
| The Effect of Resampling on Data‐imbalanced Conditions for Prediction towards Nuclear Receptor Profiling Using Deep Learning YO Lee, YJ Kim Molecular Informatics 39 (8), 1900131, 2020 | 8 | 2020 |
| Effects of quantization on federated learning with local differential privacy M Kim, O Günlü, RF Schaefer GLOBECOM 2022-2022 IEEE Global Communications Conference, 921-926, 2022 | 3 | 2022 |
| Privacy, secrecy, and storage with nested randomized polar subcode constructions O Günlü, P Trifonov, M Kim, RF Schaefer, V Sidorenko IEEE Transactions on Communications 70 (1), 514-525, 2021 | 3 | 2021 |
Rafael F. SchaeferTechnische Universität Dresdentu-dresden.de의 이메일 확인됨
