collabclass

Reproducibility package for the paper:

Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas. Collaborative Classification from Noisy Labels, AISTATS 2021.

This repository contains

• a reference implementation of the algorithms presented in the paper, and
• Jupyter notebooks enabling the reproduction of some of the experiments.

Getting started

Our codebase was tested with Python 3.8. The following libraries are required:

• numpy (tested with version 1.19.2)
• scipy (tested with version 1.6.2)
• matplotlib (tested with version 3.3.4)
• numba (tested with version 0.53.1)
• notebook (tested with version 6.3.0)

To get started, follow these steps:

• Clone the repo locally with: git clone https://github.com/spotify-research/collabclass.git
• Move to the repository: cd collabclass
• Install the dependencies: pip install -r requirements.txt
• Install the package: pip install -e lib/
• Move to the notebook folder: cd notebooks
• Start a notebook server: jupyter notebok

Support

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Contributing

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Author

Lucas Maystre

A full list of contributors can be found on GitHub.

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License

Copyright 2021 Spotify, Inc.

Licensed under the Apache License, Version 2.0: https://www.apache.org/licenses/LICENSE-2.0

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