Differentially Private Kernel Inducing Points using features from ScatterNets (DP-KIP-ScatterNet) for Privacy Preserving Data Distillation

Data distillation aims to generate a small data set that closely mimics the performance of a given learning algorithm on the original data set. The distilled dataset is hence useful to simplify the training process thanks to its small data size. However, distilled data samples are not necessarily pr...

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Veröffentlicht in:	arXiv.org 2024-04
Hauptverfasser:	Vinaroz, Margarita, Mi Jung Park
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Distillation Kernels Privacy
Online-Zugang:	Volltext
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