shivmgg / SLDA-Tutorial

Deep Streaming Linear Discriminant Analysis: A Tutorial

This is a PyTorch tutorial on how to use the Deep Streaming Linear Discriminant Analysis (SLDA) algorithm from our CVPRW-2020 paper. This repo uses the original scenario definitions for the CORe50 dataset, which differ from the CORe50 experiments in our paper. To replicate our ImageNet experiments, please see this repo.

Dependences

• Tested with Python 3.7 and PyTorch 1.3.1, NumPy, NVIDIA GPU
• Install the Avalanche framework

Usage

To experiment with SLDA on CORe50, let's run:

• main_tutorial.py

Citation

If using this code, please cite our paper.

@InProceedings{Hayes_2020_CVPR_Workshops,
    author = {Hayes, Tyler L. and Kanan, Christopher},
    title = {Lifelong Machine Learning With Deep Streaming Linear Discriminant Analysis},
    booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
    month = {June},
    year = {2020}
}