BriefGPT.xyz
Feb, 2020
因果机制转移的少样本领域自适应
Few-shot Domain Adaptation by Causal Mechanism Transfer
HTML
PDF
Takeshi Teshima, Issei Sato, Masashi Sugiyama
TL;DR
本文提出了一种利用机制转移适应目标领域的方法,该方法可以在数据生成机制在不同领域间不变的假设下应对非参数移位问题,并应用因果模型中的结构方程来进行域适应,实验证明该方法可以在回归问题中有效使用。
Abstract
We study
few-shot supervised domain adaptation
(DA) for
regression problems
, where only a few labeled target domain data and many labeled source domain data are available. Many of the current DA methods base thei
→