Training Neural Networks Using Features Replay

12 July 2018

Papers citing "Training Neural Networks Using Features Replay"

16 / 16 papers shown

Title
HPFF: Hierarchical Locally Supervised Learning with Patch Feature Fusion Junhao Su Chenghao He Feiyu Zhu Xiaojie Xu Dongzhi Guan Chenyang Si 56 2 0 08 Jul 2024
PETRA: Parallel End-to-end Training with Reversible Architectures Stéphane Rivaud Louis Fournier Thomas Pumir Eugene Belilovsky Michael Eickenberg Edouard Oyallon 25 0 0 04 Jun 2024
FedImpro: Measuring and Improving Client Update in Federated Learning Zhenheng Tang Yonggang Zhang S. Shi Xinmei Tian Tongliang Liu Bo Han Xiaowen Chu FedML 26 13 0 10 Feb 2024
Local Learning with Neuron Groups Adeetya Patel Michael Eickenberg Eugene Belilovsky 29 5 0 18 Jan 2023
Block-wise Training of Residual Networks via the Minimizing Movement Scheme Skander Karkar Ibrahim Ayed Emmanuel de Bézenac Patrick Gallinari 33 1 0 03 Oct 2022
Layer-Wise Partitioning and Merging for Efficient and Scalable Deep Learning S. Akintoye Liangxiu Han H. Lloyd Xin Zhang Darren Dancey Haoming Chen Daoqiang Zhang FedML 34 5 0 22 Jul 2022
SplitEasy: A Practical Approach for Training ML models on Mobile Devices Kamalesh Palanisamy Vivek Khimani Moin Hussain Moti Dimitris Chatzopoulos 22 20 0 09 Nov 2020
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning Bin Gu An Xu Zhouyuan Huo Cheng Deng Heng-Chiao Huang FedML 38 27 0 14 Aug 2020
Pipelined Backpropagation at Scale: Training Large Models without Batches Atli Kosson Vitaliy Chiley Abhinav Venigalla Joel Hestness Urs Koster 35 33 0 25 Mar 2020
Pipelined Training with Stale Weights of Deep Convolutional Neural Networks Lifu Zhang T. Abdelrahman 21 0 0 29 Dec 2019
Fully Decoupled Neural Network Learning Using Delayed Gradients Huiping Zhuang Yi Wang Qinglai Liu Shuai Zhang Zhiping Lin FedML 16 30 0 21 Jun 2019
Associated Learning: Decomposing End-to-end Backpropagation based on Auto-encoders and Target Propagation Yu-Wei Kao Hung-Hsuan Chen BDL 20 5 0 13 Jun 2019
Improving Discrete Latent Representations With Differentiable Approximation Bridges Jason Ramapuram Russ Webb DRL 19 9 0 09 May 2019
Decoupled Greedy Learning of CNNs Eugene Belilovsky Michael Eickenberg Edouard Oyallon 6 114 0 23 Jan 2019
Benefits of depth in neural networks Matus Telgarsky 153 602 0 14 Feb 2016
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 270 13,368 0 25 Aug 2014