Perfectly Parallel Fairness Certification of Neural Networks

5 December 2019

Papers citing "Perfectly Parallel Fairness Certification of Neural Networks"

24 / 24 papers shown

Title
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification Anan Kabaha Dana Drachsler-Cohen AAML 53 0 0 23 Feb 2025
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations Vasisht Duddu Oskari Jarvinen Lachlan J. Gunn Nirmal Asokan 74 1 0 25 Jun 2024
Probabilistic Verification of Neural Networks using Branch and Bound David Boetius Stefan Leue Tobias Sutter 45 1 0 27 May 2024
DelBugV: Delta-Debugging Neural Network Verifiers R. Elsaleh Guy Katz 45 1 0 29 May 2023
Provable Fairness for Neural Network Models using Formal Verification Giorgian Borca-Tasciuc Xingzhi Guo Stanley Bak Steven Skiena 32 4 0 16 Dec 2022
Abstract Interpretation-Based Feature Importance for SVMs Abhinanda Pal Francesco Ranzato Caterina Urban Marco Zanella FAtt 29 0 0 22 Oct 2022
Explainable Global Fairness Verification of Tree-Based Classifiers Stefano Calzavara Lorenzo Cazzaro Claudio Lucchese Federico Marcuzzi 40 2 0 27 Sep 2022
Verifying Attention Robustness of Deep Neural Networks against Semantic Perturbations S. Munakata Caterina Urban Haruki Yokoyama Koji Yamamoto Kazuki Munakata AAML 24 4 0 13 Jul 2022
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networks Kiarash Mohammadi Aishwarya Sivaraman G. Farnadi 30 5 0 01 Jun 2022
Certifying Some Distributional Fairness with Subpopulation Decomposition Mintong Kang Linyi Li Maurice Weber Yang Liu Ce Zhang Bo Li OOD 61 15 0 31 May 2022
CertiFair: A Framework for Certified Global Fairness of Neural Networks Haitham Khedr Yasser Shoukry FedML 31 20 0 20 May 2022
Individual Fairness Guarantees for Neural Networks Elias Benussi A. Patané Matthew Wicker Luca Laurenti Marta Kwiatkowska University of Oxford 28 21 0 11 May 2022
Quantitative Strongest Post Linpeng Zhang Benjamin Lucien Kaminski LRM 11 13 0 14 Feb 2022
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 35 18 0 08 Feb 2022
An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks Matan Ostrovsky Clark W. Barrett Guy Katz 45 26 0 06 Jan 2022
Latent Space Smoothing for Individually Fair Representations Momchil Peychev Anian Ruoss Mislav Balunović Maximilian Baader Martin Vechev FaML 38 19 0 26 Nov 2021
Self-Correcting Neural Networks For Safe Classification Klas Leino Aymeric Fromherz Ravi Mangal Matt Fredrikson Bryan Parno C. Păsăreanu 40 4 0 23 Jul 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 24 36 0 10 Jun 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 46 55 0 06 Apr 2021
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo Li AAML 38 128 0 09 Sep 2020
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 Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 352 4,237 0 23 Aug 2019
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 251 1,842 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 933 0 21 Oct 2016