bimp

Code to reproduce the experiments of ICLR2023-paper: How I Learned to Stop Worrying and Love Retraining

https://github.com/zib-iol/bimp

Science Score: 38.0%

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  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
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  • Academic publication links
    Links to: arxiv.org
  • Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
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    Low similarity (8.1%) to scientific vocabulary

Keywords

deep-learning learning-rate-scheduling neural-network optimization pruning pytorch sparsity
Last synced: 6 months ago · JSON representation ·

Repository

Code to reproduce the experiments of ICLR2023-paper: How I Learned to Stop Worrying and Love Retraining

Basic Info
  • Host: GitHub
  • Owner: ZIB-IOL
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 60.5 KB
Statistics
  • Stars: 8
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
deep-learning learning-rate-scheduling neural-network optimization pruning pytorch sparsity
Created about 4 years ago · Last pushed almost 3 years ago
Metadata Files
Readme Citation

README.md

[ICLR2023] How I Learned to Stop Worrying and Love Retraining

Authors: Max Zimmer, Christoph Spiegel, Sebastian Pokutta

This repository contains the code to reproduce the experiments from the ICLR2023 paper "How I Learned to Stop Worrying and Love Retraining". The code is based on PyTorch 1.9 and the experiment-tracking platform Weights & Biases. The code to reproduce semantic segmentation as well as NLP experiments will be added soon.

Structure and Usage

Experiments are started from the following file: - main.py: Starts experiments using the dictionary format of Weights & Biases.

The rest of the project is structured as follows: - strategies: Contains all used sparsification methods. - runners: Contains classes to control the training and collection of metrics. - metrics: Contains all metrics as well as FLOP computation methods. - models: Contains all model architectures used. - utilities: Contains useful auxiliary functions and classes.

Citation

In case you find the paper or the implementation useful for your own research, please consider citing:

@inproceedings{zimmer2023how, title={How I Learned to Stop Worrying and Love Retraining}, author={Max Zimmer and Christoph Spiegel and Sebastian Pokutta}, booktitle={The Eleventh International Conference on Learning Representations }, year={2023}, url={https://openreview.net/forum?id=_nF5imFKQI} }

Owner

  • Name: IOL Lab
  • Login: ZIB-IOL
  • Kind: organization
  • Location: Germany

Working on optimization and learning at the intersection of mathematics and computer science

Citation (citation.bib)

@inproceedings{zimmer2023how,
title={How I Learned to Stop Worrying and Love Retraining},
author={Max Zimmer and Christoph Spiegel and Sebastian Pokutta},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=_nF5imFKQI}
}

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Max Zimmer m****r@m****g 7
Max Zimmer m****r@c****e 2
Max 6****m 2
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