ResearchTrend.AI
On the Compressive Power of Deep Rectifier Networks for High Resolution Representation of Class Boundaries

On the Compressive Power of Deep Rectifier Networks for High Resolution Representation of Class Boundaries

Senjian An
Bennamoun
F. Boussaïd
ArXivPDFHTML

Papers citing "On the Compressive Power of Deep Rectifier Networks for High Resolution Representation of Class Boundaries"

3 / 3 papers shown
Title
Identity Mappings in Deep Residual Networks
Identity Mappings in Deep Residual Networks
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
283
10,149
0
16 Mar 2016
Learning Functions: When Is Deep Better Than Shallow
Learning Functions: When Is Deep Better Than Shallow
H. Mhaskar
Q. Liao
T. Poggio
51
144
0
03 Mar 2016
The Power of Depth for Feedforward Neural Networks
The Power of Depth for Feedforward Neural Networks
Ronen Eldan
Ohad Shamir
143
731
0
12 Dec 2015

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.