aai-institute / aai-institute/pyDVL
Paper repro: DUL
- Dominant language
- Python
- Stars
- 146
- Forks
- 10
- PR merge metrics
- No merged PRs in 30d
Description
_Wang, Tianhao, Yu Yang, and Ruoxi Jia. “Improving Cooperative Game Theory-Based Data Valuation via Data Utility Learning.” arXiv, 2022. https://doi.org/10.48550/arXiv.2107.06336._
- [x] #157
- [x] #138
- [ ] Run all experiments
Contributor guide
Research direction
The issue references a paper and two completed tasks (#157, #138). Start by reading the linked arXiv paper to understand the DUL method. Then examine the closed issues to see what implementations or experiments were already done. The remaining task is to run all experiments, which likely involves setting up experimental pipelines, possibly in an experiments/ directory, and ensuring reproducibility. Check for existing experiment scripts or configuration files in the repository.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 10/100