Apr 1, 2023 · GradMDM is a technique that adjusts the direction and the magnitude of the gradients to effectively find a small perturbation for each input.

GradMDM is a technique that adjusts the direction and the magnitude of the gradients to effectively find a small perturbation for each input.

Aug 4, 2023 · In this paper, we explore the robustness of dynamic neural networks against energy-oriented attacks targeted at reducing their efficiency.

Sep 1, 2023 · In this paper, we explore the robustness of dynamic neural networks against energy-oriented attacks targeted at reducing their efficiency.

In this paper, we explore the robustness of dynamic neural networks against energy-oriented attacks targeted at reducing their efficiency. Specifically, we ...

Sep 1, 2023 · GradMDM: Adversarial Attack on Dynamic Networks. Research output ... Specifically, we attack dynamic models with our novel algorithm GradMDM.

GradMDM: Adversarial Attack on Dynamic Networks. Pan, J., Foo, L., Zheng, Q., Fan, Z., Rahmani, H., Ke, Q., & Liu, J. IEEE Transactions on Pattern Analysis ...

This repository contains the result and the sample code for the work: GradMDM: Adversarial Attack on Dynamic Networks ...

Mar 31, 2023 · Dynamic neural networks can greatly reduce computation redundancy without compromising accuracy by adapting their structures based on the ...

Gradmdm: Adversarial attack on dynamic networks. J Pan, LG Foo, Q Zheng, Z Fan, H Rahmani, Q Ke, J Liu. IEEE Transactions on Pattern Analysis and Machine ...