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cs.LG2025
Beyond One-Size-Fits-All: Neural Networks for Differentially Private Tabular Data Synthesis
Kai Chen, Chen Gong, Tianhao Wang
In differentially private (DP) tabular data synthesis, the consensus is that statistical models are better than neural network (NN)-based methods. However, we argue that this concl…
cs.LG2021
DeepObliviate: A Powerful Charm for Erasing Data Residual Memory in Deep Neural Networks
Yingzhe He, Guozhu Meng, Kai Chen +2
Machine unlearning has great significance in guaranteeing model security and protecting user privacy. Additionally, many legal provisions clearly stipulate that users have the righ…