Compact Memory for Continual Logistic Regression

This is an implemenation for "Compact Memory for Continual Logistic Regression"

Description for implementation

• example_four_moons.ipynb : results for four-moon task

• setting_dataset.py : task generators

• main_splitcifar100_basereplay_batch.py : baseline experience replay for Split-CIFAR-100

• main_splitcifar100_baselambda_batch.py : baseline K-prior for Split-CIFAR-100

• main_splitcifar100_ourem_batch.py : our method for Split-CIFAR-100

• run_main_splitcifar100.sh : execute experimentsr for Split-CIFAR-100

Once you replace generate_setting_splitcifar100 in each main_**.py using another dataset generator in setting_dataset.py, the code can be run and evaluated on other datasets as well.