https://github.com/applied-machine-learning-lab/m3oe

Code for SIGIR 2024 paper: M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework
https://github.com/applied-machine-learning-lab/m3oe

Last synced: 9 months ago
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Code for SIGIR 2024 paper: M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework

• Host: GitHub
• URL: https://github.com/applied-machine-learning-lab/m3oe
• Owner: Applied-Machine-Learning-Lab
• Created: 2024-04-28T13:18:53.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-09-14T08:40:09.000Z (over 1 year ago)
• Last Synced: 2025-06-20T04:38:33.751Z (9 months ago)
• Language: Python
• Homepage: https://arxiv.org/abs/2404.18465
• Size: 16.4 MB
• Stars: 38
• Watchers: 0
• Forks: 6
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

          
Code for SIGIR 2024 paper M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework

Run experiments on MovieLens-1M:

```

cd examples

mkdir model_para

mkdir output

bash run_MDMT.sh

```

The 5 rounds results will be saved under examples/output