An Information Theory-inspired Strategy for Automatic Network Pruning

An Information Theory-inspired Strategy for Automatic Network Pruning

19 August 2021

Papers citing "An Information Theory-inspired Strategy for Automatic Network Pruning"

10 / 10 papers shown

Title
Dynamic Low-Rank Sparse Adaptation for Large Language Models Weizhong Huang Yuxin Zhang Xiawu Zheng Yong-Jin Liu Jing Lin Yiwu Yao Rongrong Ji 97 1 0 21 Feb 2025
Learning Sparse Neural Networks with Identity Layers Mingjian Ni Guangyao Chen Xiawu Zheng Peixi Peng Liuliang Yuan Yonghong Tian 19 0 0 14 Jul 2023
Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective Yuexiao Ma Huixia Li Xiawu Zheng Xuefeng Xiao Rui Wang Shilei Wen Xin Pan Rongrong Ji Rongrong Ji MQ 27 12 0 21 Mar 2023
Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey Dalin Zhang Kaixuan Chen Yan Zhao B. Yang Li-Ping Yao Christian S. Jensen 48 3 0 22 Aug 2022
Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy Thibault Castells Seul-Ki Yeom 3DV 18 3 0 18 Nov 2021
OMPQ: Orthogonal Mixed Precision Quantization Yuexiao Ma Taisong Jin Xiawu Zheng Yan Wang Huixia Li Yongjian Wu Guannan Jiang Wei Zhang Rongrong Ji MQ 19 33 0 16 Sep 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,027 0 06 Mar 2020
Channel Pruning via Automatic Structure Search Mingbao Lin Rongrong Ji Yuxin Zhang Baochang Zhang Yongjian Wu Yonghong Tian 76 241 0 23 Jan 2020
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications Tien-Ju Yang Andrew G. Howard Bo Chen Xiao Zhang Alec Go Mark Sandler Vivienne Sze Hartwig Adam 90 515 0 09 Apr 2018
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,572 0 17 Apr 2017