Compact and Computationally Efficient Representation of Deep Neural Networks

27 May 2018

Papers citing "Compact and Computationally Efficient Representation of Deep Neural Networks"

15 / 15 papers shown

Title
Asynchronous Training Schemes in Distributed Learning with Time Delay Haoxiang Wang Zhanhong Jiang Chao Liu S. Sarkar D. Jiang Young M. Lee 42 2 0 28 Aug 2022
Efficient Adaptive Federated Optimization of Federated Learning for IoT Zunming Chen Hongyan Cui Ensen Wu Yu Xi 27 0 0 23 Jun 2022
Compacting Deep Neural Networks for Internet of Things: Methods and Applications Ke Zhang Hanbo Ying Hongning Dai Lin Li Yuangyuang Peng Keyi Guo Hongfang Yu 21 38 0 20 Mar 2021
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons Simon Wiedemann Suhas Shivapakash P. Wiedemann Daniel Becking Wojciech Samek F. Gerfers Thomas Wiegand MQ 23 7 0 17 Dec 2020
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training Simon Wiedemann Temesgen Mehari Kevin Kepp Wojciech Samek 27 18 0 09 Apr 2020
Progressive Graph Convolutional Networks for Semi-Supervised Node Classification Negar Heidari Alexandros Iosifidis GNN 29 14 0 27 Mar 2020
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 71 973 0 04 Oct 2019
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek 51 93 0 27 Jul 2019
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek MQ 19 21 0 15 May 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 24 1,335 0 07 Mar 2019
Multi-Kernel Prediction Networks for Denoising of Burst Images Talmaj Marinc Vignesh Srinivasan Serhan Gül C. Hellge Wojciech Samek 30 26 0 05 Feb 2019
Entropy-Constrained Training of Deep Neural Networks Simon Wiedemann Arturo Marbán K. Müller Wojciech Samek 27 27 0 18 Dec 2018
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication Felix Sattler Simon Wiedemann K. Müller Wojciech Samek MQ 36 212 0 22 May 2018
Universal Deep Neural Network Compression Yoojin Choi Mostafa El-Khamy Jungwon Lee MQ 86 86 0 07 Feb 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017