ReLoss - Official implementation for paper "Relational Surrogate Loss Learning" ICLR 2022

Overview

Relational Surrogate Loss Learning (ReLoss)

Official implementation for paper "Relational Surrogate Loss Learning" in International Conference on Learning Representations (ICLR) 2022.

By Tao Huang, Zekang Li, Hua Lu, Yong Shan, Shusheng Yang, Yang Feng, Fei Wang, Shan You, Chang Xu.


Usage

Install ReLoss

pip install git+https://github.com/hunto/ReLoss.git

Or install for development:

git clone https://github.com/hunto/ReLoss
cd ReLoss
pip install -e .

Training with ReLoss

All the inputs and outputs of ReLoss are the same as the original loss.

  • classification
    from reloss.cls import ReLoss
    loss_fn = ReLoss()
  • human pose estimation
    from reloss.pose import ReLoss
    loss_fn = ReLoss(heatmap_size=(64, 48))

Citation

@inproceedings{
huang2022relational,
title={Relational Surrogate Loss Learning},
author={Tao Huang and Zekang Li and Hua Lu and Yong Shan and Shusheng Yang and Yang Feng and Fei Wang and Shan You and Chang Xu},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=dZPgfwaTaXv}
}
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Comments
  • train_reloss.py is not runnable

    train_reloss.py is not runnable

    Hi, Thanks for sharing your awesome work. I notice there are many typos and un-existed parameters in train_reloss.py, such as the code from line 33-40. 'i' is not defined, and 'logits, targets' from the corresponding batch are not used in the following code.

    opened by lwmlyy 12
  • Update spearman.py

    Update spearman.py

    In https://arxiv.org/abs/2203.09630, we propose monotonic differentiable sorting networks which perform better than logistic with ART. Thus, we changed the default interpolation_type to cauchy in our recent update to diffsort. While cauchy might work better, I suggest specifying the interpolation type explicitly for reproducibility.

    Best regards,

    Felix

    opened by Felix-Petersen 2
Owner
Tao Huang
Machine Learning & Computer Vision
Tao Huang
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