BriefGPT.xyz
Jun, 2015
奥卡姆之门
Occam's Gates
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Jonathan Raiman, Szymon Sidor
TL;DR
本文通过对门控单元激活值的L1正则化来解决基于注意力的RNN模型过拟合的问题,同时提高了模型的可解释性。实验证明,这种方法在多项任务中均有效,包含情感分析、释义识别和问答等。
Abstract
We present a complimentary objective for training
recurrent neural networks
(RNN) with gating units that helps with
regularization
and
interpreta
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