aai-institute / aai-institute/pyDVL

SGD and variance reduced SGD for IFs

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#366 0 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看
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

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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.

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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

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