Compression-aware Training of Neural Networks using Frank-Wolfe

24 May 2022

Papers citing "Compression-aware Training of Neural Networks using Frank-Wolfe"

11 / 11 papers shown

Title
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture Yikun Hou Suvrit Sra A. Yurtsever 29 0 0 28 Jan 2025
PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs Max Zimmer Megi Andoni Christoph Spiegel S. Pokutta VLM 52 10 0 23 Dec 2023
ELSA: Partial Weight Freezing for Overhead-Free Sparse Network Deployment Paniz Halvachi Alexandra Peste Dan Alistarh Christoph H. Lampert 20 0 0 11 Dec 2023
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging Max Zimmer Christoph Spiegel S. Pokutta MoMe 41 14 0 29 Jun 2023
Low Rank Optimization for Efficient Deep Learning: Making A Balance between Compact Architecture and Fast Training Xinwei Ou Zhangxin Chen Ce Zhu Yipeng Liu 21 2 0 22 Mar 2023
CrAM: A Compression-Aware Minimizer Alexandra Peste Adrian Vladu Eldar Kurtic Christoph H. Lampert Dan Alistarh 24 8 0 28 Jul 2022
Renormalized Sparse Neural Network Pruning Michael Rawson 4 0 0 21 Jun 2022
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 141 684 0 31 Jan 2021
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 188 1,027 0 06 Mar 2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning Alex Renda Jonathan Frankle Michael Carbin 224 383 0 05 Mar 2020
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014