#randomized-smoothing News & Analysis

2 articles tagged with #randomized-smoothing. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Mar 47/103

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Dual Randomized Smoothing: Beyond Global Noise Variance

Researchers propose a dual Randomized Smoothing framework that overcomes limitations of standard neural network robustness certification by using input-dependent noise variances instead of global ones. The method achieves strong performance at both small and large radii with gains of 15-20% on CIFAR-10 and 8-17% on ImageNet, while adding only 60% computational overhead.

AINeutralarXiv – CS AI · 21h ago6/10

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CEAR: Certified Ensemble Adversarial Robustness in DNNs

Researchers propose CEAR, an ensemble-based defense mechanism combining empirical and certified robustness techniques to protect deep neural networks against adversarial attacks. The method uses varying Gaussian noise, temperature adjustments, and novel voting mechanisms while extending randomized smoothing to ensemble classifiers, demonstrating improved certified accuracy across benchmark datasets.