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Malicious Network Traffic Detection via Deep Learning: An Information
  Theoretic View

Malicious Network Traffic Detection via Deep Learning: An Information Theoretic View

16 September 2020
Erick Galinkin
    AAML
ArXivPDFHTML

Papers citing "Malicious Network Traffic Detection via Deep Learning: An Information Theoretic View"

5 / 5 papers shown
Title
Adversarial Machine Learning -- Industry Perspectives
Adversarial Machine Learning -- Industry Perspectives
Ramnath Kumar
Magnus Nyström
J. Lambert
Andrew Marshall
Mario Goertzel
Andi Comissoneru
Matt Swann
Sharon Xia
AAML
SILM
64
235
0
04 Feb 2020
The Expressive Power of Neural Networks: A View from the Width
The Expressive Power of Neural Networks: A View from the Width
Zhou Lu
Hongming Pu
Feicheng Wang
Zhiqiang Hu
Liwei Wang
80
886
0
08 Sep 2017
Deep Complex Networks
Deep Complex Networks
C. Trabelsi
O. Bilaniuk
Ying Zhang
Dmitriy Serdyuk
Sandeep Subramanian
J. F. Santos
Soroush Mehri
Negar Rostamzadeh
Yoshua Bengio
C. Pal
139
829
0
27 May 2017
Deep Learning and the Information Bottleneck Principle
Deep Learning and the Information Bottleneck Principle
Naftali Tishby
Noga Zaslavsky
DRL
145
1,570
0
09 Mar 2015
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
204
14,831
1
21 Dec 2013
1