RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr

7 July 2020

Haoyi Xiong

Papers citing "RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr"

25 / 25 papers shown

Title
Towards Understanding the Transferability of Deep Representations Hong Liu Mingsheng Long Jianmin Wang Michael I. Jordan 32 25 0 26 Sep 2019
Towards Understanding the Importance of Noise in Training Neural Networks Mo Zhou Tianyi Liu Yan Li Dachao Lin Enlu Zhou T. Zhao MLT 34 26 0 07 Sep 2019
DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks Xingjian Li Haoyi Xiong Hanchao Wang Yuxuan Rao Liping Liu Zeyu Chen Jun Huan 30 171 0 26 Jan 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 94 769 0 12 Nov 2018
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning Huayu Chen Yang Song Chen Sun Andrew G. Howard Serge J. Belongie 83 476 0 16 Jun 2018
Do Better ImageNet Models Transfer Better? Simon Kornblith Jonathon Shlens Quoc V. Le OOD MLT 115 1,319 0 23 May 2018
Parameter Transfer Unit for Deep Neural Networks Yinghua Zhang Yu Zhang Qiang Yang 21 22 0 23 Apr 2018
Explicit Inductive Bias for Transfer Learning with Convolutional Networks Xuhong Li Yves Grandvalet Franck Davoine SSL 49 349 0 05 Feb 2018
The Implicit Bias of Gradient Descent on Separable Data Daniel Soudry Elad Hoffer Mor Shpigel Nacson Suriya Gunasekar Nathan Srebro 51 908 0 27 Oct 2017
Exploiting Convolution Filter Patterns for Transfer Learning Mehmet Aygun Y. Aytar H. K. Ekenel 33 12 0 23 Aug 2017
Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning Weifeng Ge Yizhou Yu 121 233 0 28 Feb 2017
Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer Sergey Zagoruyko N. Komodakis 83 2,561 0 12 Dec 2016
What makes ImageNet good for transfer learning? Minyoung Huh Pulkit Agrawal Alexei A. Efros OOD SSeg VLM SSL 75 675 0 30 Aug 2016
DisturbLabel: Regularizing CNN on the Loss Layer Lingxi Xie Jingdong Wang Zhen Wei Meng Wang Qi Tian 59 251 0 30 Apr 2016
Deep Networks with Stochastic Depth Gao Huang Yu Sun Zhuang Liu Daniel Sedra Kilian Q. Weinberger 115 2,344 0 30 Mar 2016
Training Very Deep Networks R. Srivastava Klaus Greff Jürgen Schmidhuber 79 1,675 0 22 Jul 2015
Path-SGD: Path-Normalized Optimization in Deep Neural Networks Behnam Neyshabur Ruslan Salakhutdinov Nathan Srebro ODL 43 305 0 08 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 410 9,233 0 06 Jun 2015
Cyclical Learning Rates for Training Neural Networks L. Smith ODL 94 2,515 0 03 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 102 19,448 0 09 Mar 2015
Learning Transferable Features with Deep Adaptation Networks Mingsheng Long Yue Cao Jianmin Wang Michael I. Jordan OOD 163 5,163 0 10 Feb 2015
FitNets: Hints for Thin Deep Nets Adriana Romero Nicolas Ballas Samira Ebrahimi Kahou Antoine Chassang C. Gatta Yoshua Bengio FedML 195 3,862 0 19 Dec 2014
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 81 8,309 0 06 Nov 2014
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition Jeff Donahue Yangqing Jia Oriol Vinyals Judy Hoffman Ning Zhang Eric Tzeng Trevor Darrell VLM ObjD 98 4,946 0 06 Oct 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 340 7,650 0 03 Jul 2012