204 citations · 306 across the 21 of their papers we have counts for
3 papers · 1 filter
The Taboo Trap: Behavioural Detection of Adversarial Samples
Ilia Shumailov, Yiren Zhao, Robert Mullins +1
Deep Neural Networks (DNNs) have become a powerful toolfor a wide range of problems. Yet recent work has found an increasing variety of adversarial samplesthat can fool them. Most…
Dynamic Channel Pruning: Feature Boosting and Suppression
Xitong Gao, Yiren Zhao, Łukasz Dudziak +2
Making deep convolutional neural networks more accurate typically comes at the cost of increased computational and memory resources. In this paper, we reduce this cost by exploitin…
To compress or not to compress: Understanding the Interactions between Adversarial Attacks and Neural Network Compression
Yiren Zhao, Ilia Shumailov, Robert Mullins +1
As deep neural networks (DNNs) become widely used, pruned and quantised models are becoming ubiquitous on edge devices; such compressed DNNs are popular for lowering computational…