17 citations · 47 across the 13 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 5 cited
Edge Bias in Federated Learning and its Solution by Buffered Knowledge Distillation
Sangho Lee, Kiyoon Yoo, Nojun Kwak
Federated learning (FL), which utilizes communication between the server (core) and local devices (edges) to indirectly learn from more data, is an emerging field in deep learning…
cs.LG2020★ 2 cited
On the Orthogonality of Knowledge Distillation with Other Techniques: From an Ensemble Perspective
SeongUk Park, KiYoon Yoo, Nojun Kwak
To put a state-of-the-art neural network to practical use, it is necessary to design a model that has a good trade-off between the resource consumption and performance on the test…
cs.CV2020★ 17 cited
Position-based Scaled Gradient for Model Quantization and Pruning
Jangho Kim, KiYoon Yoo, Nojun Kwak
We propose the position-based scaled gradient (PSG) that scales the gradient depending on the position of a weight vector to make it more compression-friendly. First, we theoretica…