The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

Guolz

Last update: Oct 19, 2022

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Deep Learning DS3L

Overview

DS3L

This is the code for paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

Setups

The code is implemented with Python and Pytorch.

Running D3SL for benchmark datasets

Here is an example:

python train.py --dataset MNIST --ratio 0.6 --n_labels 60 --iterations 200000

Acknowledgements

We thank the Pytorch implementation on Meta-Net (https://github.com/xjtushujun/meta-weight-ne) and learning-to-reweight-examples(https://github.com/danieltan07/learning-to-reweight-examples).

Contact

If you have any questions, please contact Lan-Zhe Guo ([email protected]).

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Comments

wnet is not updated through all process

In your paper, wnet is updated by supervised loss. However, in the code train.py, wnet is not updated through all processes. Please check weight.grad. It is always None, and it means that there is no change of went.

(add) I tested the code as follows: -remove the related parts of meta network -remove the related parts of w network (weight function alpha) -tested on CIFAR10 with 30% mismatch -applied Pi model as mentioned in the paper

then, I got the same result of 78%

opened by min9kwak 0

Owner

Guolz

I am a M.Sc. student in LAMDA Group, Nanjing University. I am interested in machine learning and deep learning. My website: www.guolz.com

GitHub

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The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

Related tags

Overview

DS3L

Setups

Running D3SL for benchmark datasets

Acknowledgements

Contact

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Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)

Comments

wnet is not updated through all process

Owner

Guolz

TensorFlow code for the neural network presented in the paper: "Structural Language Models of Code" (ICML'2020)

Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face Manipulation" published in CVPR 2020.

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