Environment Invariant Linear Least Squares

The script to reproduce the illustration section in our paper ``Environment Invariant Linear Least Squares''.

Reproduce the results in Section 5

First conduct simulations and save the results in ``~/eills_demo.npy'' using the following command:

python eills_demo.py

Then the results in Fig. 3 can be presented running the following commands

python regularization_path.py
python eills_demo_vis11.py
python eills_demo_vis12.py

For the comparsion with other invariance learning methods, we also run simulations and save the results using the command

python eills_demo2.py

We run the following commands to generate the results in Fig. 4.

python eills_demo_vis21.py
python eills_demo_vis22.py
python eills_demo_vis23.py

Reproduce the results in the supplemental material

For Fig. 3, run single gumbel approximated EILLS using

python test_eills_gb.py --mode 3 --seed 1

For Fig. 4, first run the simulations and then visualize the saved results

python unit_test_eills.py --mode 0
python unit_test_eills.py --mode 1