aai-institute / aai-institute/pyDVL

Paper repro: DUL

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#206 0 comments 0 reactions 0 assignees View on GitHub
meta paper reproduction
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

Open the contributing 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

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