Learning Representations that Support Robust Transfer of Predictors

Related tags

Deep LearningTRM
Overview

Transfer Risk Minimization (TRM)

Code for Learning Representations that Support Robust Transfer of Predictors

Prepare the Datasets

Preprocess the SceneCOCO dataset :

# preprocess COCO
python coco.py
# preprocess Places
python places.py

# generate SceceCOCO dataset
python cocoplaces.py

Running the Experiments

python -m domainbed.scripts.train  --data_dir {root} --algorithm {alg} \
	--dataset {dataset} --trial_seed {t_seed} --epochs {epochs}  (--resnet50)

root: root directory for the data
alg: ERM, VREx, IRM, GroupDRO, Fish, MLDG, TRM
t_seed: seed for data splitting
dataset: PACS or OfficeHome or ColoredMNIST or SceneCOCO
resnet50: use ResNet50 (default: ResNet18)
epochs: training epochs

This implementation is based on / inspired by:

Owner
Yilun Xu
Hello!
Yilun Xu
GitHub Repository
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