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Status : OnlineAuthors: Dongqing Zhang, Jiaolong Yang, Dongqiangzi Ye, Gang Hua Download PDF Abstract: Although weight and activation quantization is an effective approach for Deep Neural Network (DNN) compression and has a lot of potentials to increase inference speed leveraging bit-operations, there is still a noticeable gap in terms of prediction accuracy ...
Status : OnlineDongqing Zhang∗, Jiaolong Yang∗, Dongqiangzi Ye∗, and Gang Hua Microsoft Research zdqzeros@gmail.comjiaoyan@microsoft.comeowinye@gmail.comganghua@microsoft.com Abstract. Although weight and activation quantization is an effective approach for Deep Neural Network (DNN) compression and has a lot of
Status : OnlineDongqing Zhang , Jiaolong Yang , Dongqiangzi Ye , and Gang Hua Microsoft Research zdqzeros@gmail.com jiaoyan@microsoft.com eowinye@gmail.com ganghua@microsoft.com Abstract. Although weight and activation quantization is an e ective approach for Deep Neural Network (DNN) compression and has a lot of
Status : OnlineDongqiangzi Ye. Gang Hua. Although weight and activation quantization is an effective approach for Deep Neural Network (DNN) compression and has a lot of potentials to increase inference speed ...
Status : OnlineLQ-Nets. By Dongqing Zhang, Jiaolong Yang, Dongqiangzi Ye, Gang Hua.. Microsoft Research Asia (MSRA). Introduction. This repository contains the training code of LQ-Nets introduced in our ECCV 2018 paper: D. Zhang*, J. Yang*, D. Ye* and G. Hua. LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks.
Status : OnlineSHAOJIE YE jayden@cs.wisc.edu "Sudarshan Sujay" Yadala sujayyadalam@cs.wisc.edu. Xuechun Yang xuechun@cs.wisc.edu. Chenhao Ye chenhaoy@cs.wisc.edu. Dongqiangzi Ye dongqiangzi@cs.wisc.edu. Shang-Yen Yeh syeh@cs.wisc.edu. Hang Yin hyin56@cs.wisc.edu. Quan Yin quan@cs.wisc.edu. Bobbi Yogatama bwyogatama@cs.wisc.edu. Kyonghwan Yoon ykw6644@cs.wisc ...
Status : OnlineDongqing Zhang*, Jiaolong Yang*, Dongqiangzi Ye* and Gang Hua LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks The 15th European Conference on Computer Vision (ECCV2018), Munich, Germany [Suppl. Material] (*: Equal contributions) Although weight and activation quantization is an effective approach for Deep ...
Status : OnlineAlexNet is a classic convolutional neural network architecture. It consists of convolutions, max pooling and dense layers as the basic building blocks. Grouped convolutions are used in order to fit the model across two GPUs.
Status : OnlineTroubleshoot
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