gradient perturbation

Differentially Private Subspace Fine-Tuning for Large Language Models AAAI 2026 Boosting Adversarial Transferability via Residual Perturbation Attack ICCV 2025 Understanding Silent Data Corruption in LLM Training ACL 2025 Differentially Private Natural Language Models: Recent Advances and Future Directions EACL 2024 Towards the Robustness of Differentially Private Federated Learning AAAI 2024 Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning CVPR 2024 DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization ACL 2023 Global-Local Characteristic Excited Cross-Modal Attacks from Images to Videos AAAI 2023 GPMO: Gradient Perturbation-Based Contrastive Learning for Molecule Optimization IJCAI 2023 Improving the Model Consistency of Decentralized Federated Learning ICML 2023 Initialization Noise in Image Gradients and Saliency Maps CVPR 2023 Make Landscape Flatter in Differentially Private Federated Learning CVPR 2023 Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning ICML 2023 Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization IJCAI 2021 Large Scale Private Learning via Low-rank Reparametrization ICML 2021 LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy IJCAI 2021 Learning Model-Based Privacy Protection under Budget Constraints AAAI 2021 Principal component analysis in the stochastic differential privacy model UAI 2021 Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective CVPR 2021 Gradient Perturbation is Underrated for Differentially Private Convex Optimization IJCAI 2020 Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019 Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization NeurIPS 2018