2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CV2022★ 2 cited
It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher
Kanghyun Choi, Hye Yoon Lee, Deokki Hong +4
Model quantization is considered as a promising method to greatly reduce the resource requirements of deep neural networks. To deal with the performance drop induced by quantizatio…
cs.LG2020
DANCE: Differentiable Accelerator/Network Co-Exploration
Kanghyun Choi, Deokki Hong, Hojae Yoon +3
To cope with the ever-increasing computational demand of the DNN execution, recent neural architecture search (NAS) algorithms consider hardware cost metrics into account, such as…
cs.LG2018
Network Recasting: A Universal Method for Network Architecture Transformation
Joonsang Yu, Sungbum Kang, Kiyoung Choi
This paper proposes network recasting as a general method for network architecture transformation. The primary goal of this method is to accelerate the inference process through th…