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cs.LG2025
LyAm: Robust Non-Convex Optimization for Stable Learning in Noisy Environments
Elmira Mirzabeigi, Sepehr Rezaee, Kourosh Parand
Training deep neural networks, particularly in computer vision tasks, often suffers from noisy gradients and unstable convergence, which hinder performance and generalization. In t…
cs.LG2025
Scanning Trojaned Models Using Out-of-Distribution Samples
Hossein Mirzaei, Ali Ansari, Bahar Dibaei Nia +10
Scanning for trojan (backdoor) in deep neural networks is crucial due to their significant real-world applications. There has been an increasing focus on developing effective gener…