💻 Mixture of Groups

Mixture of Groups for Learning in Crowdsourcing Scenarios

Authors

Francisco Mena and Ricardo Ñanculef

📜 Source

• Preliminary work in a conference, only group modeling
  • 🔓 Final published version
  • Presentation
• Extended work in a journal, group modeling + individual annotators
  • 🔒 Final published version
  • 🔓 Preprint

🖊️ Citation

Mena, Francisco, and Ricardo Ñanculef. "Revisiting Machine Learning from Crowds a Mixture Model for Grouping Annotations." Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 24th Iberoamerican Congress, CIARP 2019, Havana, Cuba, October 28-31, 2019, Proceedings 24. Springer International Publishing, 2019.

@inproceedings{mena2019revisiting,
  title={Revisiting Machine Learning from Crowds a Mixture Model for Grouping Annotations},
  author={Mena, Francisco and {\~N}anculef, Ricardo},
  booktitle={Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 24th Iberoamerican Congress, CIARP 2019, Havana, Cuba, October 28-31, 2019, Proceedings 24},
  pages={493--503},
  year={2019},
  organization={Springer},
  doi={10.1007/978-3-030-33904-3_46}
}

this is a reference to our initial work in a conference

Mena, Francisco, Ricardo Ñanculef, and Carlos Valle. "Collective annotation patterns in learning from crowds." Intelligent Data Analysis 24.S1 (2020): 63-86.

@article{mena2020collective,
  title={Collective annotation patterns in learning from crowds},
  author={Mena, Francisco and {\~N}anculef, Ricardo and Valle, Carlos},
  journal={Intelligent Data Analysis},
  volume={24},
  number={S1},
  pages={63--86},
  year={2020},
  publisher={IOS Press},
  doi={10.3233/IDA-200009}
}

this is a reference of our extended work with text+image data