Gradual DropIn of Layers to Train Very Deep Neural Networks

Gradual DropIn of Layers to Train Very Deep Neural Networks

22 November 2015

Papers citing "Gradual DropIn of Layers to Train Very Deep Neural Networks"

12 / 12 papers shown

Title
On Efficient Training of Large-Scale Deep Learning Models: A Literature Review Li Shen Yan Sun Zhiyuan Yu Liang Ding Xinmei Tian Dacheng Tao VLM 30 41 0 07 Apr 2023
A Survey on Dropout Methods and Experimental Verification in Recommendation Yong Li Weizhi Ma C. L. Philip Chen Hao Fei Yiqun Liu Shaoping Ma Yue Yang 33 9 0 05 Apr 2022
Automated Progressive Learning for Efficient Training of Vision Transformers Changlin Li Bohan Zhuang Guangrun Wang Xiaodan Liang Xiaojun Chang Yi Yang 28 46 0 28 Mar 2022
Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives Duo Li Qifeng Chen 153 19 0 24 Mar 2020
Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations Bohan Zhuang Jing Liu Mingkui Tan Lingqiao Liu Ian Reid Chunhua Shen MQ 29 44 0 10 Aug 2019
Effective and Efficient Dropout for Deep Convolutional Neural Networks Shaofeng Cai Jinyang Gao Gang Chen Beng Chin Ooi Wei Wang Meihui Zhang BDL 18 53 0 06 Apr 2019
AccUDNN: A GPU Memory Efficient Accelerator for Training Ultra-deep Neural Networks Jinrong Guo Wantao Liu Wang Wang Q. Lu Songlin Hu Jizhong Han Ruixuan Li 16 9 0 21 Jan 2019
Gradual Learning of Recurrent Neural Networks Ziv Aharoni Gal Rattner Haim Permuter AI4CE 27 4 0 29 Aug 2017
Mollifying Networks Çağlar Gülçehre Marcin Moczulski Francesco Visin Yoshua Bengio 23 46 0 17 Aug 2016
Regularization for Unsupervised Deep Neural Nets Baiyang Wang Diego Klabjan BDL 23 25 0 15 Aug 2016
Deep Networks with Stochastic Depth Gao Huang Yu Sun Zhuang Liu Daniel Sedra Kilian Q. Weinberger 74 2,336 0 30 Mar 2016
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012