Optimizing the Adversarial Perturbation with a Momentum-based Adaptive Matrix
Published:Dec 16, 2025 08:35
•1 min read
•ArXiv
Analysis
This article, sourced from ArXiv, likely presents a novel method for improving adversarial attacks in the context of machine learning. The focus is on optimizing the perturbations used to fool models, potentially leading to more effective attacks and a better understanding of model vulnerabilities. The use of a momentum-based adaptive matrix suggests a dynamic approach to perturbation generation, which could improve efficiency and effectiveness.
Key Takeaways
- •Focuses on improving adversarial attacks.
- •Uses a momentum-based adaptive matrix.
- •Aims to optimize perturbations for more effective attacks.
Reference
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