4 citations · 6 across the 3 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★ 4 cited
SimEx: Express Prediction of Inter-dataset Similarity by a Fleet of Autoencoders
Inseok Hwang, Jinho Lee, Frank Liu +1
Knowing the similarity between sets of data has a number of positive implications in training an effective model, such as assisting an informed selection out of known datasets favo…
cs.LG2019
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design
Mayoore S. Jaiswal, Bumsoo Kang, Jinho Lee +1
Target encoding is an effective technique to deliver better performance for conventional machine learning methods, and recently, for deep neural networks as well. However, the exis…