64 citations · 205 across the 9 of their papers we have counts for
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cs.CV2020★ 63 cited
Asymmetric Loss For Multi-Label Classification
Emanuel Ben-Baruch, Tal Ridnik, Nadav Zamir +4
In a typical multi-label setting, a picture contains on average few positive labels, and many negative ones. This positive-negative imbalance dominates the optimization process, an…
cs.CV2020
TResNet: High Performance GPU-Dedicated Architecture
Tal Ridnik, Hussam Lawen, Asaf Noy +3
Many deep learning models, developed in recent years, reach higher ImageNet accuracy than ResNet50, with fewer or comparable FLOPS count. While FLOPs are often seen as a proxy for…
cs.LG2020★ 18 cited
Knapsack Pruning with Inner Distillation
Yonathan Aflalo, Asaf Noy, Ming Lin +2
Neural network pruning reduces the computational cost of an over-parameterized network to improve its efficiency. Popular methods vary from -norm sparsification to Neural A…