BriefGPT.xyz
Feb, 2022
同意不同意:通过异议实现更好的可转移性的多样性
Agree to Disagree: Diversity through Disagreement for Better Transferability
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Matteo Pagliardini, Martin Jaggi, François Fleuret, Sai Praneeth Karimireddy
TL;DR
本文提出D-BAT算法,通过学习一组包含多样化的预测特征的模型,解决了梯度学习在样本库之外泛化的问题,同时在多个实验中得到了证实。
Abstract
gradient-based learning
algorithms have an implicit simplicity bias which in effect can limit the diversity of predictors being sampled by the learning procedure. This behavior can hinder the
transferability
of t
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