Individual Fairness Guarantees for Neural Networks

International Joint Conference on Artificial Intelligence (IJCAI), 2022

11 May 2022

Marta Kwiatkowska University of Oxford

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Papers citing "Individual Fairness Guarantees for Neural Networks"

20 / 20 papers shown

Title
SMiLE: Provably Enforcing Global Relational Properties in Neural Networks Matteo Francobaldi Michele Lombardi Andrea Lodi NAI AAML 135 0 0 10 Nov 2025
Correct-By-Construction: Certified Individual Fairness through Neural Network Training Ruihan Zhang Jun Sun FaML 220 1 0 21 Aug 2025
Monitoring Robustness and Individual FairnessKnowledge Discovery and Data Mining (KDD), 2025 Ashutosh Gupta T. Henzinger Konstantin Kueffner Kaushik Mallik David Pape AAML 194 1 0 31 May 2025
Tightening convex relaxations of trained neural networks: a unified approach for convex and S-shaped activations Pablo Carrasco Gonzalo Muñoz 246 3 0 30 Oct 2024
FairQuant: Certifying and Quantifying Fairness of Deep Neural NetworksInternational Conference on Software Engineering (ICSE), 2024 Brian Hyeongseok Kim Jingbo Wang Chao Wang 268 3 0 05 Sep 2024
Verifying the Generalization of Deep Learning to Out-of-Distribution Domains Guy Amir Osher Maayan Tom Zelazny Guy Katz Michael Schapira AAML 388 7 0 04 Jun 2024
Procedural Fairness in Machine Learning Ziming Wang Changwu Huang Xin Yao FaML 165 3 0 02 Apr 2024
FairProof : Confidential and Certifiable Fairness for Neural Networks Chhavi Yadav A. Chowdhury Dan Boneh Kamalika Chaudhuri MLAU 306 14 0 19 Feb 2024
Certification of Distributional Individual FairnessNeural Information Processing Systems (NeurIPS), 2023 Matthew Wicker Vihari Piratla Adrian Weller 121 1 0 20 Nov 2023
When to Trust AI: Advances and Challenges for Certification of Neural NetworksConference on Computer Science and Information Systems (FedCSIS), 2023 Marta Kwiatkowska Xiyue Zhang AAML 302 11 0 20 Sep 2023
Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data SpacesAAAI Conference on Artificial Intelligence (AAAI), 2023 A. Ehyaei Kiarash Mohammadi Amir-Hossein Karimi Samira Samadi G. Farnadi AAML 173 5 0 17 Aug 2023
Adversarial Robustness Certification for Bayesian Neural NetworksWorld Congress on Formal Methods (FM), 2023 Matthew Wicker A. Patané Luca Laurenti Marta Z. Kwiatkowska AAML 213 6 0 23 Jun 2023
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic ProgrammingInternational Conference on Machine Learning (ICML), 2023 Steven Adams A. Patané Morteza Lahijanian Luca Laurenti AAML 290 8 0 19 Jun 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 598 43 0 29 Apr 2023
Individual Fairness in Bayesian Neural Networks Alice Doherty Matthew Wicker Luca Laurenti A. Patané 215 5 0 21 Apr 2023
Use Perturbations when Learning from ExplanationsNeural Information Processing Systems (NeurIPS), 2023 Juyeon Heo Vihari Piratla Matthew Wicker Adrian Weller AAML 184 2 0 11 Mar 2023
Robust Explanation Constraints for Neural NetworksInternational Conference on Learning Representations (ICLR), 2022 Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 207 23 0 16 Dec 2022
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and PerspectiveACM Computing Surveys (ACM CSUR), 2022 Zeyu Tang Jiji Zhang Kun Zhang FaML 378 35 0 08 Jun 2022
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural NetworksConference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2022 Kiarash Mohammadi Aishwarya Sivaraman G. Farnadi 230 8 0 01 Jun 2022
CertiFair: A Framework for Certified Global Fairness of Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2022 Haitham Khedr Yasser Shoukry FedML 151 26 0 20 May 2022