35 citations · 61 across the 7 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 3 cited
How Does Supernet Help in Neural Architecture Search?
Yuge Zhang, Quanlu Zhang, Yaming Yang
Weight sharing, as an approach to speed up architecture performance estimation has received wide attention. Instead of training each architecture separately, weight sharing builds…
cs.CL2020★ 19 cited
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression
Yihuan Mao, Yujing Wang, Chufan Wu +6
BERT is a cutting-edge language representation model pre-trained by a large corpus, which achieves superior performances on various natural language understanding tasks. However, a…
cs.LG2020★ 35 cited
Deeper Insights into Weight Sharing in Neural Architecture Search
Yuge Zhang, Zejun Lin, Junyang Jiang +5
With the success of deep neural networks, Neural Architecture Search (NAS) as a way of automatic model design has attracted wide attention. As training every child model from scrat…