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May, 2023
数据集精炼的全面研究：性能、隐私、鲁棒性和公平性
A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness
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Zongxiong Chen, Jiahui Geng, Herbert Woisetschlaeger, Sonja Schimmler, Ruben Mayer...
TL;DR
通过分析压缩数据集技术对隐私、模型鲁棒性和公平性的影响，本文提出了一个评估这一技术的大规模基准测评框架。
Abstract
The aim of
dataset distillation
is to encode the rich features of an original dataset into a tiny dataset. It is a promising approach to accelerate
neural network training
and related studies. Different approache
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