2 papers
cs.CV2026
Boosting Adversarial Transferability with Low-Cost Optimization via Maximin Expected Flatness
Chunlin Qiu, Ang Li, Yiheng Duan +4
Transfer-based attacks craft adversarial examples on white-box surrogate models and directly deploy them against black-box target models, offering model-agnostic and query-free thr…
cs.LG2025
Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data
Abhijit Chunduru, Majid Morafah, Mahdi Morafah +2
The inevitable presence of data heterogeneity has made federated learning very challenging. There are numerous methods to deal with this issue, such as local regularization, better…