17 citations · 22 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 3 cited
A Selective Survey on Versatile Knowledge Distillation Paradigm for Neural Network Models
Jeong-Hoe Ku, JiHun Oh, YoungYoon Lee +2
This paper aims to provide a selective survey about knowledge distillation(KD) framework for researchers and practitioners to take advantage of it for developing new optimized mode…
cs.LG2020★ 2 cited
Weight Equalizing Shift Scaler-Coupled Post-training Quantization
Jihun Oh, SangJeong Lee, Meejeong Park +2
Post-training, layer-wise quantization is preferable because it is free from retraining and is hardware-friendly. Nevertheless, accuracy degradation has occurred when a neural netw…
cs.LG2019★ 17 cited
Advancing GraphSAGE with A Data-Driven Node Sampling
Jihun Oh, Kyunghyun Cho, Joan Bruna
As an efficient and scalable graph neural network, GraphSAGE has enabled an inductive capability for inferring unseen nodes or graphs by aggregating subsampled local neighborhoods…