aai-institute / aai-institute/pyDVL
SGD and variance reduced SGD for IFs
未关闭
enhancement
good first issue
new-method
- 主要语言
- Python
- 星标
- 146
- 派生
- 10
- PR 合并指标
- 30 天内没有已合并 PR
描述
To complete all methods in Fisher's paper
贡献指南
调研方向
The issue references implementing SGD and variance reduced SGD for Influence Functions (IFs) to complete methods from a paper. Start by reading the referenced paper to understand the algorithms. Look at existing influence function implementations in the codebase, likely in modules related to influence or valuation. Identify where gradient-based optimization methods are currently used or missing. 'Done' means the new SGD variants are implemented, tested, and integrated with the existing influence function computation pipeline.
由索引模型根据 Issue 内容生成。
评估
- 技术栈
- python
- 领域
- machine-learning
- Issue 类型
- 功能
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 活跃度
- 停滞
- 描述清晰度
- 需要澄清
- 新手友好度
- 30/100