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FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input
  Sensitivity in Neural Networks

FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input Sensitivity in Neural Networks

3 December 2019
Mahum Naseer
M. Minhas
Faiq Khalid
Muhammad Abdullah Hanif
Osman Hasan
Muhammad Shafique
    AAML
ArXivPDFHTML

Papers citing "FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input Sensitivity in Neural Networks"

4 / 4 papers shown
Title
Special Session: Towards an Agile Design Methodology for Efficient,
  Reliable, and Secure ML Systems
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems
Shail Dave
Alberto Marchisio
Muhammad Abdullah Hanif
Amira Guesmi
Aviral Shrivastava
Ihsen Alouani
Muhammad Shafique
23
13
0
18 Apr 2022
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
314
4,203
0
23 Aug 2019
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
226
1,835
0
03 Feb 2017
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
178
932
0
21 Oct 2016
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