DSD $^2$ : Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?

2 March 2023

Papers citing "DSD$^2$: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?"

9 / 9 papers shown

Title
Efficient Adaptation of Deep Neural Networks for Semantic Segmentation in Space Applications Leonardo Olivi Edoardo Santero Mormile Enzo Tartaglione SSeg 35 0 0 22 Apr 2025
LaCoOT: Layer Collapse through Optimal Transport Victor Quétu Nour Hezbri Enzo Tartaglione 31 0 0 13 Jun 2024
The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth Victor Quétu Zhu Liao Enzo Tartaglione 41 4 0 27 Apr 2024
NEPENTHE: Entropy-Based Pruning as a Neural Network Depth's Reducer Zhu Liao Victor Quétu Van-Tam Nguyen Enzo Tartaglione 41 2 0 24 Apr 2024
Understanding the Role of Optimization in Double Descent Chris Liu Jeffrey Flanigan 32 0 0 06 Dec 2023
The Quest of Finding the Antidote to Sparse Double Descent Victor Quétu Marta Milovanović 28 0 0 31 Aug 2023
Sparse Double Descent in Vision Transformers: real or phantom threat? Victor Quétu Marta Milovanović Enzo Tartaglione 16 2 0 26 Jul 2023
Prune Your Model Before Distill It Jinhyuk Park Albert No VLM 43 27 0 30 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