Go Wide, Then Narrow: Efficient Training of Deep Thin Networks

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks

1 July 2020

Mingxing Tan

Dale Schuurmans

Papers citing "Go Wide, Then Narrow: Efficient Training of Deep Thin Networks"

8 / 8 papers shown

Title
Elephant Neural Networks: Born to Be a Continual Learner Qingfeng Lan A. R. Mahmood CLL 51 9 0 02 Oct 2023
When does deep learning fail and how to tackle it? A critical analysis on polymer sequence-property surrogate models Himanshu T. Patra AI4CE 15 0 0 12 Oct 2022
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks Y. Fu Haichuan Yang Jiayi Yuan Meng Li Cheng Wan Raghuraman Krishnamoorthi Vikas Chandra Yingyan Lin 36 19 0 02 Jun 2022
Towards Efficient Post-training Quantization of Pre-trained Language Models Haoli Bai Lu Hou Lifeng Shang Xin Jiang Irwin King M. Lyu MQ 82 47 0 30 Sep 2021
AutoFormer: Searching Transformers for Visual Recognition Minghao Chen Houwen Peng Jianlong Fu Haibin Ling ViT 36 259 0 01 Jul 2021
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Jiachun Wang Fajie Yuan Jian Chen Qingyao Wu Min Yang Yang Sun Guoxiao Zhang BDL 40 26 0 14 Dec 2020
ShiftAddNet: A Hardware-Inspired Deep Network Haoran You Xiaohan Chen Yongan Zhang Chaojian Li Sicheng Li Zihao Liu Zhangyang Wang Yingyan Lin OOD MQ 76 76 0 24 Oct 2020
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016