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Feeding What You Need by Understanding What You Learned

Feeding What You Need by Understanding What You Learned

5 March 2022
Xiaoqiang Wang
Bang Liu
Fangli Xu
Bowei Long
Siliang Tang
Lingfei Wu
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Papers citing "Feeding What You Need by Understanding What You Learned"

4 / 4 papers shown
Title
Curriculum Learning: A Survey
Curriculum Learning: A Survey
Petru Soviany
Radu Tudor Ionescu
Paolo Rota
N. Sebe
ODL
63
337
0
25 Jan 2021
Consistency-based Semi-supervised Active Learning: Towards Minimizing
  Labeling Cost
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost
M. Gao
Zizhao Zhang
Guo-Ding Yu
Sercan Ö. Arik
L. Davis
Tomas Pfister
151
195
0
16 Oct 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
228
31,150
0
16 Jan 2013
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