Fire Together Wire Together: A Dynamic Pruning Approach with
Self-Supervised Mask Prediction

Fire Together Wire Together: A Dynamic Pruning Approach with Self-Supervised Mask Prediction

15 October 2021

Mostafa Elhoushi

Papers citing "Fire Together Wire Together: A Dynamic Pruning Approach with Self-Supervised Mask Prediction"

10 / 10 papers shown

Title
PROM: Prioritize Reduction of Multiplications Over Lower Bit-Widths for Efficient CNNs Lukas Meiner Jens Mehnert A. P. Condurache MQ 42 0 0 06 May 2025
Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models Alireza Ganjdanesh Reza Shirkavand Shangqian Gao Heng Huang DiffM VLM 56 4 0 17 Jun 2024
Stochastic Subnetwork Annealing: A Regularization Technique for Fine Tuning Pruned Subnetworks Tim Whitaker Darrell Whitley 33 0 0 16 Jan 2024
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 15 12 0 21 Mar 2023
Rewarded meta-pruning: Meta Learning with Rewards for Channel Pruning Athul Shibu Abhishek Kumar Heechul Jung Dong-Gyu Lee 17 1 0 26 Jan 2023
OLLA: Optimizing the Lifetime and Location of Arrays to Reduce the Memory Usage of Neural Networks Benoit Steiner Mostafa Elhoushi Jacob Kahn James Hegarty 29 8 0 24 Oct 2022
Compact Model Training by Low-Rank Projection with Energy Transfer K. Guo Zhenquan Lin Xiaofen Xing Fang Liu Xiangmin Xu 27 2 0 12 Apr 2022
Self-supervised Feature-Gate Coupling for Dynamic Network Pruning Mengnan Shi Chang-rui Liu Jianbin Jiao QiXiang Ye 32 1 0 29 Nov 2021
SCOP: Scientific Control for Reliable Neural Network Pruning Yehui Tang Yunhe Wang Yixing Xu Dacheng Tao Chunjing Xu Chao Xu Chang Xu AAML 50 166 0 21 Oct 2020
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 20,567 0 17 Apr 2017