The Binary and Ternary Quantization Can Improve Feature Discrimination

18 April 2025

Papers citing "The Binary and Ternary Quantization Can Improve Feature Discrimination"

7 / 7 papers shown

Title
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 314 724 0 31 Jan 2021
Binary Neural Networks: A Survey Haotong Qin Ruihao Gong Xianglong Liu Xiao Bai Jingkuan Song N. Sebe MQ 129 470 0 31 Mar 2020
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
Fixed Point Quantization of Deep Convolutional Networks D. Lin S. Talathi V. Annapureddy MQ 104 816 0 19 Nov 2015
Neural Networks with Few Multiplications Zhouhan Lin Matthieu Courbariaux Roland Memisevic Yoshua Bengio 92 331 0 11 Oct 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,508 0 04 Sep 2014
Modeling sparse connectivity between underlying brain sources for EEG/MEG Stefan Haufe Ryota Tomioka Guido Nolte K. Müller M. Kawanabe 72 113 0 12 Dec 2009