Distilled Pruning: Using Synthetic Data to Win the Lottery

7 July 2023

Papers citing "Distilled Pruning: Using Synthetic Data to Win the Lottery"

16 / 16 papers shown

Title
Dataset Distillation with Convexified Implicit Gradients Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 57 42 0 13 Feb 2023
Data Distillation: A Survey Noveen Sachdeva Julian McAuley DD 81 75 0 11 Jan 2023
Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? Mansheej Paul F. Chen Brett W. Larsen Jonathan Frankle Surya Ganguli Gintare Karolina Dziugaite UQCV 91 38 0 06 Oct 2022
Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks Mansheej Paul Brett W. Larsen Surya Ganguli Jonathan Frankle Gintare Karolina Dziugaite 52 24 0 02 Jun 2022
Dataset Distillation using Neural Feature Regression Yongchao Zhou E. Nezhadarya Jimmy Ba DD FedML 69 157 0 01 Jun 2022
Dataset Distillation by Matching Training Trajectories George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu FedML DD 170 387 0 22 Mar 2022
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? Xiaolong Ma Geng Yuan Xuan Shen Tianlong Chen Xuxi Chen ... Ning Liu Minghai Qin Sijia Liu Zhangyang Wang Yanzhi Wang 134 64 0 01 Jul 2021
What can linear interpolation of neural network loss landscapes tell us? Tiffany J. Vlaar Jonathan Frankle MoMe 56 27 0 30 Jun 2021
The Elastic Lottery Ticket Hypothesis Xiaohan Chen Yu Cheng Shuohang Wang Zhe Gan Jingjing Liu Zhangyang Wang OOD 47 34 0 30 Mar 2021
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 126 243 0 30 Oct 2020
Bespoke vs. Prêt-à-Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding Michela Paganini Jessica Zosa Forde UQCV 31 6 0 06 Jul 2020
Linear Mode Connectivity and the Lottery Ticket Hypothesis Jonathan Frankle Gintare Karolina Dziugaite Daniel M. Roy Michael Carbin MoMe 144 617 0 11 Dec 2019
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 210 3,457 0 09 Mar 2018
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.0K 193,426 0 10 Dec 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 294 6,660 0 08 Jun 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.4K 100,213 0 04 Sep 2014