A PyTorch Implementation of MIPLGP

This is a PyTorch implementation of our paper "Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision. Science China Information Sciences, in press."

Authors: Wei Tang, Weijia Zhang, and Min-Ling Zhang

@article{tang2023mipl,
  title={Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision},
  author={Wei Tang and Weijia Zhang and Min-Ling Zhang},
  journal={Science China Information Sciences},
  year={2023}
}

Requirements

gpytorch==1.8.0
numpy==1.21.5
scipy==1.7.3
torch==1.12.0

To install the requirement packages, please run the following command:

pip install -r requirements.txt

Datasets

The datasets used in this paper can be found on this link.

Demo

To reproduce the results of MNIST_MIPL dataset in the paper, please run the following command:

bash demo.sh

This package is only free for academic usage. Have fun!