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The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions

The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions

Vanessa D’Amario
S. Srivastava
Tomotake Sasaki
Xavier Boix
    AAML
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Papers citing "The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions"

4 / 4 papers shown
Title
Dimensionality compression and expansion in Deep Neural Networks
Dimensionality compression and expansion in Deep Neural Networks
Stefano Recanatesi
M. Farrell
Madhu S. Advani
Timothy Moore
Guillaume Lajoie
E. Shea-Brown
49
73
0
02 Jun 2019
Reconciling modern machine learning practice and the bias-variance trade-off
Reconciling modern machine learning practice and the bias-variance trade-off
M. Belkin
Daniel J. Hsu
Siyuan Ma
Soumik Mandal
227
1,644
0
28 Dec 2018
Understanding deep learning requires rethinking generalization
Understanding deep learning requires rethinking generalization
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
HAI
334
4,624
0
10 Nov 2016
Object Detection Through Exploration With A Foveated Visual Field
Object Detection Through Exploration With A Foveated Visual Field
Emre Akbas
Miguel P. Eckstein
ObjD
52
69
0
04 Aug 2014

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