1 citations · 1 across the 5 of their papers we have counts for
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BicKD: Bilateral Contrastive Knowledge Distillation
Jiangnan Zhu, Yukai Xu, Li Xiong +4
Knowledge distillation (KD) is a machine learning framework that transfers knowledge from a teacher model to a student model. The vanilla KD proposed by Hinton et al. has been the…
Sharpness-Aware Parameter Selection for Machine Unlearning
Saber Malekmohammadi, Hong kyu Lee, Li Xiong
It often happens that some sensitive personal information, such as credit card numbers or passwords, are mistakenly incorporated in the training of machine learning models and need…
Node-level Contrastive Unlearning on Graph Neural Networks
Hong kyu Lee, Qiuchen Zhang, Carl Yang +1
Graph unlearning aims to remove a subset of graph entities (i.e. nodes and edges) from a graph neural network (GNN) trained on the graph. Unlike machine unlearning for models train…
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
Hong kyu Lee, Qiuchen Zhang, Carl Yang +2
Machine unlearning aims to eliminate the influence of a subset of training samples (i.e., unlearning samples) from a trained model. Effectively and efficiently removing the unlearn…