Oct 25, 2023 · We propose a novel hierarchical learning method, Hierarchical Machine Unlearning (HMU), with the known distribution of unlearning requests.
Oct 25, 2023 · We propose a novel hierarchical learning method, Hierarchical Machine Unlearning (HMU), with the known distribution of unlearning requests.
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What is the machine unlearning method?
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Which model should be retrained in the exact unlearning process?
We propose to train the model using the hierarchical data set after partitioning, which further reduces the loss of prediction accuracy of the existing methods.
Oct 10, 2024 · We propose HUF, a hierarchical unlearning framework to effectively process MU requests, by adopting a hierarchical classification architecture.
Machine unlearning (MU) is the task of causing a trained ML model to forget individual data points or a class of data in the training data, without adversely ...
Machine unlearning refers to the process of selectively removing specific training data points and their influence on an already trained model, making the.
Hierarchical Machine Unlearning. H. Zhu, Y. Xia, Y. Li, W. Li, K. Liu, and X. Gao. LION, volume 14286 of Lecture Notes in Computer Science, page 92-106 ...
May 13, 2024 · Machine unlearning can be broadly described as removing the influences of training data from a trained model. At its core, unlearning on a ...
Yet, having models unlearn is notoriously difficult. We introduce SISA training, a framework that expedites the unlearning process by strategically limiting the ...
Sep 25, 2024 · This paper explores the challenges and solutions associated with implementing machine unlearning in three widely used neural network architectures.