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Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models

By Guihong Li and others at
LogoUniversity of Texas at Austin
The rapid growth of machine learning has spurred legislative initiatives such as ``the Right to be Forgotten,'' allowing users to request data removal. In response, ``machine unlearning'' proposes the selective removal of unwanted data without the need for retraining from scratch. While the Neural-Tangent-Kernel-based (NTK-based) unlearning method excels in performance,... Show more
December 22, 2023
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Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models
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