112 citations · 237 across the 20 of their papers we have counts for
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Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer
Chen Zhu, Zheng Xu, Ali Shafahi +3
When large scale training data is available, one can obtain compact and accurate networks to be deployed in resource-constrained environments effectively through quantization and p…
Encoding Robustness to Image Style via Adversarial Feature Perturbations
Manli Shu, Zuxuan Wu, Micah Goldblum +1
Adversarial training is the industry standard for producing models that are robust to small adversarial perturbations. However, machine learning practitioners need models that are…
Headless Horseman: Adversarial Attacks on Transfer Learning Models
Ahmed Abdelkader, Michael J. Curry, Liam Fowl +5
Transfer learning facilitates the training of task-specific classifiers using pre-trained models as feature extractors. We present a family of transferable adversarial attacks agai…