An Inter-Layer Weight Prediction and Quantization for Deep Neural Networks based on a Smoothly Varying Weight Hypothesis

16 July 2019

Papers citing "An Inter-Layer Weight Prediction and Quantization for Deep Neural Networks based on a Smoothly Varying Weight Hypothesis"

10 / 10 papers shown

Title
Improving Neural Network Quantization without Retraining using Outlier Channel Splitting Ritchie Zhao Yuwei Hu Jordan Dotzel Christopher De Sa Zhiru Zhang OODD MQ 73 307 0 28 Jan 2019
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design Ningning Ma Xiangyu Zhang Haitao Zheng Jian Sun 128 4,957 0 30 Jul 2018
AMC: AutoML for Model Compression and Acceleration on Mobile Devices Yihui He Ji Lin Zhijian Liu Hanrui Wang Li Li Song Han 65 1,348 0 10 Feb 2018
Learning Efficient Convolutional Networks through Network Slimming Zhuang Liu Jianguo Li Zhiqiang Shen Gao Huang Shoumeng Yan Changshui Zhang 96 2,407 0 22 Aug 2017
The Microsoft 2017 Conversational Speech Recognition System Wayne Xiong Lingfeng Wu F. Alleva J. Droppo Xuedong Huang A. Stolcke 54 467 0 21 Aug 2017
Depthwise Separable Convolutions for Neural Machine Translation Lukasz Kaiser Aidan Gomez François Chollet 56 278 0 09 Jun 2017
Pruning Filters for Efficient ConvNets Hao Li Asim Kadav Igor Durdanovic H. Samet H. Graf 3DPC 162 3,687 0 31 Aug 2016
Fixed Point Quantization of Deep Convolutional Networks D. Lin S. Talathi V. Annapureddy MQ 71 814 0 19 Nov 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 194 8,793 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 226 6,628 0 08 Jun 2015