194 citations · 730 across the 35 of their papers we have counts for
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cs.CV2023★ 8 cited
The Role of Pre-training Data in Transfer Learning
Rahim Entezari, Mitchell Wortsman, Olga Saukh +3
The transfer learning paradigm of model pre-training and subsequent fine-tuning produces high-accuracy models. While most studies recommend scaling the pre-training size to benefit…
cs.CV2022★ 3 cited
Understanding the effect of sparsity on neural networks robustness
Lukas Timpl, Rahim Entezari, Hanie Sedghi +2
This paper examines the impact of static sparsity on the robustness of a trained network to weight perturbations, data corruption, and adversarial examples. We show that, up to a c…