gradual_domain_adaptation

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Dataset instructions

• Code for the paper "Understanding Self-Training for Gradual Domain Adaptation"
• The portraits dataset is an existing dataset, and can be downloaded from https://www.dropbox.com/s/ubjjoo0b2wz4vgz/faces_aligned_small_mirrored_co_aligned_cropped_cleaned.tar.gz?dl=0
• After downloading, extract the tar file, and copy the "M" and "F" folders inside a folder called dataset_32x32 inside the code folder (current folder, where the README is). Then run "python create_dataset.py"
• Create a folder called "saved_files" in the current code folder.
• Experiments on other datasets should work without downloading additional datasets.
• For the final camera-ready code, we will include virtualenv instructions, and a more automated process for processing the dataset.

Main files

• gradual_shift_better.py contains scripts for experiments in Section 5.1 and 5.3.
• regularization_helps.py contains scripts for experiments in Section 5.2.