| Privacy-preserving logistic regression training with a faster gradient variant J Chiang arXiv preprint arXiv:2201.10838, 2022 | 10 | 2022 |
| Volley revolver: A novel matrix-encoding method for privacy-preserving neural networks (inference) J Chiang arXiv preprint arXiv:2201.12577, 2022 | 7 | 2022 |
| Quadratic Gradient: Combining Gradient Algorithms and Newton's Method as One J Chiang arXiv preprint arXiv:2209.03282, 2022 | 6* | 2022 |
| Multinomial logistic regression algorithms via quadratic gradient J Chiang arXiv preprint arXiv:2208.06828, 2022 | 4 | 2022 |
| On polynomial approximation of activation function J Chiang arXiv preprint arXiv:2202.00004, 2022 | 4 | 2022 |
| Activation functions not to active: A plausible theory on interpreting neural networks J Chiang arXiv preprint arXiv:2305.00663, 2023 | 3 | 2023 |
| Privacy-preserving cnn training with transfer learning J Chiang arXiv preprint arXiv:2304.03807, 2023 | 3 | 2023 |
| A Simple Solution for Homomorphic Evaluation on Large Intervals J Chiang arXiv preprint arXiv:2405.15201, 2024 | 2 | 2024 |
| Privacy-Preserving Logistic Regression Training on Large Datasets J Chiang arXiv preprint arXiv:2406.13221, 2024 | 1 | 2024 |
| LFFR: Logistic Function For (multi-output) Regression J Chiang arXiv preprint arXiv:2407.21187, 2024 | | 2024 |
| LFFR: Logistic Function For (single-output) Regression J Chiang arXiv preprint arXiv:2407.09955, 2024 | | 2024 |
| Privacy-Preserving 3-Layer Neural Network Training using Mere Homomorphic Encryption Technique J Chiang arXiv preprint arXiv:2308.09531, 2023 | | 2023 |
