class_forgetting

[Deep Unlearning-PyTorch] Class Forgetting as in paper "Deep Unlearning: Fast and Efficient Training-free Approach to Controlled Forgetting"

https://github.com/sangamesh-kodge/class_forgetting

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[Deep Unlearning-PyTorch] Class Forgetting as in paper "Deep Unlearning: Fast and Efficient Training-free Approach to Controlled Forgetting"

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Created over 2 years ago · Last pushed almost 2 years ago
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Readme Citation

Readme.md

Introduction

This is official repository for the paper Deep Unlearning: Fast and Efficient Gradient-free Approach to Class Forgetting accepted at TMLR.

Setup Environment using yml

bash conda env create -f env.yml conda activate forget

Demo of unlearning algorithm

bash python3 ./demo.py

Unlearning Single class on CIFAR10, CIFAR100 and ImageNet.

```bash

for CIFAR10

sh ./scripts/our_cifar10.sh ```

```bash

for CIFAR100

sh ./scripts/our_cifar100.sh ```

```bash

for ImageNet

sh ./scripts/our_imagenet.sh ```

Analysis

Scripts for analysis done in the paper can be found in scripts/analysis.

An older version of the repository can be found in the legacy branch of the repository.

Citation

Kindly cite the paper if you use the code. Thanks!

APA

Kodge, Sangamesh, Gobinda Saha, and Kaushik Roy. "Deep Unlearning: Fast and Efficient Gradient-Free Class Forgetting."

Bibtex

@article{ kodge2024deep, title={Deep Unlearning: Fast and Efficient Gradient-free Class Forgetting}, author={Sangamesh Kodge and Gobinda Saha and Kaushik Roy}, journal={Transactions on Machine Learning Research}, issn={2835-8856}, year={2024}, url={https://openreview.net/forum?id=BmI5p6wBi0}, note={} }

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  • Login: sangamesh-kodge
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