Pytorch implementation of LLP-VAT
- Kuen-Han Tsai and Hsuan-Tien Lin. Learning from label proportions with consistency regularization. In Proceedings of the Asian Conference on Machine Learning (ACML), November 2020 [ pdf ]
- Python version: 3.6.2
- GPU: GeForce GTX 1080
- Prerequisite:
pip install -r requirements.txt
Make sure to generate the LLP data before running the experiment of LLP-VAT.
python -m llp_vat.preprocessing --dataset_name cifar10 --alg uniform --bag_size 64
Required arguments:
Parameter | Description |
---|---|
--dataset_name | svhn , cifar10 or cifar100 |
--alg | the bag creation algorithm, uniform or kmeans |
Optional arguments:
Parameter | Description |
---|---|
--obj_dir | path to the proccessed object directory |
--dataset_dir | path to the raw data directory |
Arugments for the bag creation algorithm:
Algorithm | Parameter | Description |
---|---|---|
uniform | -b, --bag_size | number of instances in each bag |
uniform | --replacement | whether the sample is with replacement |
kmeans | --k, --n_clusters | number of clusters to be used |
kmeans | --reduction | number of dimensions to keep |
uniform, kmeans | --seed | pass an int for reproducible results |
python -m llp_vat.main --dataset_name cifar10 --alg uniform -b 64
Required arguments:
Parameter | Description |
---|---|
--dataset_name | svhn , cifar10 or cifar100 |
--alg | the bag creation algorithm, uniform or kmeans |
Optional arguments:
Parameter | Description | Default |
---|---|---|
--obj_dir | path to the proccessed object directory | ./obj |
--dataset_dir | path to the raw data directory | ./obj/dataset |
--result_dir | path to the result directory | ./results |
--num_epochs | number of training epochs | 400 |
--lr | value of learning rate | 0.0003 |
--optimizer | adam or sgd |
adam |
--valid | ratio of the validation set | 0.1 |
--seed | pass an int for reproducible results | 0 |
--consistency_type | vat , pi or none |
vat |
--consistency | consistecny loss weight | 0.05 |
@InProceedings{pmlr-v129-tsai20a,
title = {Learning from Label Proportions with Consistency Regularization},
author = {Tsai, Kuen-Han and Lin, Hsuan-Tien},
booktitle = {Proceedings of The 12th Asian Conference on Machine Learning},
year = {2020}
}