Security in Machine Learning and its Applications (SiMLA) 2025
Description
The 7th ACNS Workshop on Security in Machine Learning and its Applications (SiMLA 2025) focuses on the security and privacy issues of machine learning systems. It invites original contributions addressing adversarial learning, robustness analysis, and privacy-preserving techniques. The workshop aims to foster collaboration among researchers and encourage the exchange of innovative ideas in the field.
Highlights
Focuses on security and privacy issues in machine learning. Explores adversarial learning and robustness analysis. Emphasizes privacy-preserving machine learning techniques. Encourages collaboration among researchers. Seeks original contributions in the form of full and short papers. Includes a best paper award. Submissions must be anonymous. Proceedings will be published by Springer.
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