Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks

14 June 2019

Papers citing "Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks"

3 / 3 papers shown

Title
Deep Recursive Embedding for High-Dimensional Data Zixia Zhou Yuanyuan Wang B. Lelieveldt Qian Tao 24 7 0 12 Apr 2021
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks Ahmed T. Elthakeb Prannoy Pilligundla Fatemehsadat Mireshghallah Amir Yazdanbakhsh H. Esmaeilzadeh MQ 55 68 0 05 Nov 2018
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 337 1,049 0 10 Feb 2017