This repository ( https://github.com/dmpark04/alasso ) contains code to reproduce the key findings of:
Park, D., Hong, S., Han, B., & Lee, K. M. (2019). Continual learning by asymmetric loss approximation with single-side overestimation. In Proceedings of the IEEE International Conference on Computer Vision (pp. 3335-3344).
@inproceedings{park2019continual,
title={Continual learning by asymmetric loss approximation with single-side overestimation},
author={Park, Dongmin and Hong, Seokil and Han, Bohyung and Lee, Kyoung Mu},
booktitle={Proceedings of the IEEE International Conference on Computer Vision},
pages={3335--3344},
year={2019}
}
We have tested this code with the following configuration:
- Python 3.6.9
- Tensorflow 1.13.1
- Keras 2.0.5
git clone https://github.com/dmpark04/alasso.git
For 30 tasks, run the following commands.
cd permuted_minst
python train.py
python 'Basic graph Permuted MNIST.py'
For 100 tasks, run the following commands.
cd permuted_minst
python train_100.py
python 'Basic graph Permuted MNIST.py'