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Perfectly Parallel Fairness Certification of Neural Networks

Perfectly Parallel Fairness Certification of Neural Networks

5 December 2019
Caterina Urban
M. Christakis
Valentin Wüstholz
Fuyuan Zhang
ArXivPDFHTML

Papers citing "Perfectly Parallel Fairness Certification of Neural Networks"

17 / 17 papers shown
Title
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification
Anan Kabaha
Dana Drachsler-Cohen
AAML
43
0
0
23 Feb 2025
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Vasisht Duddu
Oskari Jarvinen
Lachlan J. Gunn
Nirmal Asokan
69
1
0
25 Jun 2024
Probabilistic Verification of Neural Networks using Branch and Bound
Probabilistic Verification of Neural Networks using Branch and Bound
David Boetius
Stefan Leue
Tobias Sutter
42
0
0
27 May 2024
Explainable Global Fairness Verification of Tree-Based Classifiers
Explainable Global Fairness Verification of Tree-Based Classifiers
Stefano Calzavara
Lorenzo Cazzaro
Claudio Lucchese
Federico Marcuzzi
24
2
0
27 Sep 2022
Verifying Attention Robustness of Deep Neural Networks against Semantic
  Perturbations
Verifying Attention Robustness of Deep Neural Networks against Semantic Perturbations
S. Munakata
Caterina Urban
Haruki Yokoyama
Koji Yamamoto
Kazuki Munakata
AAML
15
4
0
13 Jul 2022
CertiFair: A Framework for Certified Global Fairness of Neural Networks
CertiFair: A Framework for Certified Global Fairness of Neural Networks
Haitham Khedr
Yasser Shoukry
FedML
18
19
0
20 May 2022
Individual Fairness Guarantees for Neural Networks
Individual Fairness Guarantees for Neural Networks
Elias Benussi
A. Patané
Matthew Wicker
Luca Laurenti
Marta Kwiatkowska University of Oxford
20
21
0
11 May 2022
Quantitative Strongest Post
Quantitative Strongest Post
Linpeng Zhang
Benjamin Lucien Kaminski
LRM
11
13
0
14 Feb 2022
Verification-Aided Deep Ensemble Selection
Verification-Aided Deep Ensemble Selection
Guy Amir
Tom Zelazny
Guy Katz
Michael Schapira
AAML
30
18
0
08 Feb 2022
An Abstraction-Refinement Approach to Verifying Convolutional Neural
  Networks
An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks
Matan Ostrovsky
Clark W. Barrett
Guy Katz
32
26
0
06 Jan 2022
Latent Space Smoothing for Individually Fair Representations
Latent Space Smoothing for Individually Fair Representations
Momchil Peychev
Anian Ruoss
Mislav Balunović
Maximilian Baader
Martin Vechev
FaML
36
19
0
26 Nov 2021
Fair Normalizing Flows
Fair Normalizing Flows
Mislav Balunović
Anian Ruoss
Martin Vechev
AAML
13
36
0
10 Jun 2021
A Review of Formal Methods applied to Machine Learning
A Review of Formal Methods applied to Machine Learning
Caterina Urban
Antoine Miné
35
55
0
06 Apr 2021
Learning Certified Individually Fair Representations
Learning Certified Individually Fair Representations
Anian Ruoss
Mislav Balunović
Marc Fischer
Martin Vechev
FaML
15
92
0
24 Feb 2020
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
323
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
228
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
180
932
0
21 Oct 2016
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