517 citations · 1.7k across the 49 of their papers we have counts for
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cs.LG2021★ 7 cited
Faster Meta Update Strategy for Noise-Robust Deep Learning
Youjiang Xu, Linchao Zhu, Lu Jiang +1
It has been shown that deep neural networks are prone to overfitting on biased training data. Towards addressing this issue, meta-learning employs a meta model for correcting the t…
cs.LG2018
A Unified Analysis of Stochastic Momentum Methods for Deep Learning
Yan Yan, Tianbao Yang, Zhe Li +2
Stochastic momentum methods have been widely adopted in training deep neural networks. However, their theoretical analysis of convergence of the training objective and the generali…
cs.LG2018★ 517 cited
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu, Juho Lee, Minseop Park +4
The goal of few-shot learning is to learn a classifier that generalizes well even when trained with a limited number of training instances per class. The recently introduced meta-l…