23 citations · 45 across the 12 of their papers we have counts for
3 papers · 1 filter
Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study
Hongjun Choi, Eun Som Jeon, Ankita Shukla +1
Mixup is a popular data augmentation technique based on creating new samples by linear interpolation between two given data samples, to improve both the generalization and robustne…
A Style-aware Discriminator for Controllable Image Translation
Kunhee Kim, Sanghun Park, Eunyeong Jeon +2
Current image-to-image translations do not control the output domain beyond the classes used during training, nor do they interpolate between different domains well, leading to imp…
Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor Data
Eun Som Jeon, Anirudh Som, Ankita Shukla +3
Deep neural networks are parametrized by several thousands or millions of parameters, and have shown tremendous success in many classification problems. However, the large number o…