预遗忘阶段(Pre-unlearning Stage):在遗忘过程开始之前检测恶意请求或制定遗忘规则。 遗忘阶段(In-unlearning Stage):监控模型变化,如果检测到异常则停止遗忘过程。 后遗忘阶段(Post-unlearning Stage):保护遗忘后模型的信息泄露,或恢复模型到攻击前的状态。 3.3 威胁模型 (1)攻击角色(Attack Roles) 数据贡献者 (R1)...
3. 对于整体 Machine Unlearning 的工作流大致分为三个部分: 《A survey of machine unlearning》 从 学习 -> 遗忘 ->验证 三个步骤实现整体的 unlearning全流程,其中: a)学习过程依旧是基于目前已知的学习和训练算法; b)遗忘过程分为 Exact unlearning 和 Approximate unlearning,遗忘的任务包括数据点、用户、特征...
② 从技术层面看,Machine Unlearning 领域的研究不仅限于隐私保护,还包括分析不同数据对模型收敛时所贡献的梯度。这种分析有助于实现更精准的去学习,同时也能增强模型对噪声数据的检测能力(Noisy Data Detection)。 02 什么是 Machine Unlearning? 2024 年 5 月发布的综述《Machine Unlearning: A Comprehensive Survey...
另一方面,机器遗忘(machine unlearning, MU)是从训练好的ML模型中去除某些数据点或特征的过程,而不影响其性能[4]。MU是一个相对较新的、具有挑战性的研究领域,它关注于开发从训练有素的模型中删除敏感或不相关数据的技术。MU的目标是确保经过训练的模型不受偏见和敏感信息的影响,这些信息可能会导致负面结果[5]。
not yet featured the use of machine unlearning but could benefit greatly from it. We hope this survey serves as a valuable resource for ML researchers and those seeking to innovate privacy technologies. Our resources are publicly available at https://github.com/tamlhp/awesome-machine-unlearning. ...
Model Pruning (DBLP:conf/iwqos/LiuMYWL21; DBLP:conf/www/Wang0XQ22; DBLP:journals/corr/abs-2002-02730)Replaces partial parameters with pre-calculated parametersReduces the cost caused by intermediate storage; the unlearning process can be completed at a faster speedOnly applicable to partial models...
A resource repository for machine unlearning in large language models awesomealignmentmachine-unlearningunlearningllmlarge-language-modelllm-unlearning UpdatedJan 16, 2025 A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024. ...
Machine unlearning is a service offered to customers to withdraw their privacy from trained models, but its value is yet to be thoroughly evaluated. In addition, the free unlearning service is insufficient due to unaffordable computational cost and degra
然而,大多数现有方法仍存在不同层面的局限,而仍在发展中的 LLM 的部分特性则为 Machine Unlearning 带来了更多挑战。在。2023 年 10 月发布的综述《Large Language Model Unlearning》、2024 年的综述《《Digital Forgetting in Large Language Models: A Survey of Unlearning Methods》以及近期的工作中均指出了 ...
Learn to Unlearn: A Survey on Machine Unlearning Machine Learning (ML) models contain private information, and implementing the right to be forgotten is a challenging privacy issue in many data applicatio... Y Qu,X Yuan,M Ding,... - 《Arxiv》 被引量: 0发表: 2023年 LEARNING TO LEARN AG...