Ulrich Aïvodji

According to our database, Ulrich Aïvodji authored at least 35 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

When Interpretability Is Unequally Distributed: Fairness in Hybrid Interpretable Models.

Ziba Jabbar Zare, Ulrich Aïvodji, Julien Ferry, Thibaut Vidal

CoRR, May, 2026

Test-Time Collective Action: Proxy-Based Perturbations for Correcting Algorithmic Harms.

Meghana Bhange, Ulrich Aïvodji, Elliot Creager

CoRR, May, 2026

Towards Fair In-Context Learning with Tabular Foundation Models.

Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji

Trans. Mach. Learn. Res., 2026

Crowding Out the Noise: Algorithmic Collective Action Under Differential Privacy.

Rushabh Solanki, Meghana Bhange, Ulrich Aïvodji, Elliot Creager

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

Quantifying the Privacy of Counterfactuals by Leveraging Membership Inference Attacks Against Synthetic Data.

Maryam Babaei, Yingke Wang, Hadrien Lautraite, Héber Hwang Arcolezi, Ulrich Aïvodji, Sébastien Gambs

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

2025

Conscious Data Contribution via Community-Driven Chain-of-Thought Distillation.

Lena Libon, Meghana Bhange, Rushabh Solanki, Elliot Creager, Ulrich Aïvodji

CoRR, December, 2025

Adaptive Group Robust Ensemble Knowledge Distillation.

Patrik Joslin Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou

Trans. Mach. Learn. Res., 2025

Taming the Triangle: On the Interplays Between Fairness, Interpretability, and Privacy in Machine Learning.

Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

Comput. Intell., 2025

2024

Fairness Under Demographic Scarce Regime.

Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji

Trans. Mach. Learn. Res., 2024

A Survey on Fairness Without Demographics.

Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji

Trans. Mach. Learn. Res., 2024

Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods.

Julien Ferry, Gabriel Laberge, Ulrich Aïvodji

Trans. Mach. Learn. Res., 2024

Smooth Sensitivity for Learning Differentially-Private yet Accurate Rule Lists.

Timothée Ly, Julien Ferry, Marie-José Huguet, Sébastien Gambs, Ulrich Aïvodji

CoRR, 2024

Probabilistic Dataset Reconstruction from Interpretable Models.

Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

2023

Improving fairness generalization through a sample-robust optimization method.

Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

Mach. Learn., June, 2023

ML-Based Performance Modeling in SDN-Enabled Data Center Networks.

Kokouvi Bénoît Nougnanke, Yann Labit, Marc Bruyere, Ulrich Aïvodji, Simone Ferlin

IEEE Trans. Netw. Serv. Manag., March, 2023

SoK: Taming the Triangle - On the Interplays between Fairness, Interpretability and Privacy in Machine Learning.

Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

CoRR, 2023

Exploiting Fairness to Enhance Sensitive Attributes Reconstruction.

Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Fooling SHAP with Stealthily Biased Sampling.

Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand, Foutse Khomh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Washing The Unwashable : On The (Im)possibility of Fairwashing Detection.

Ali Shahin Shamsabadi, Mohammad Yaghini, Natalie Dullerud, Sierra Calanda Wyllie, Ulrich Aïvodji, Aisha Alaagib, Sébastien Gambs, Nicolas Papernot

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Leveraging Integer Linear Programming to Learn Optimal Fair Rule Lists.

Ulrich Aïvodji, Julien Ferry, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2022

Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations.

Jessica Dai, Sohini Upadhyay, Ulrich Aïvodji, Stephen H. Bach, Himabindu Lakkaraju

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

Local Data Debiasing for Fairness Based on Generative Adversarial Training.

Ulrich Aïvodji, François Bidet, Sébastien Gambs, Rosin Claude Ngueveu, Alain Tapp

Algorithms, 2021

Characterizing the risk of fairwashing.

Ulrich Aïvodji, Hiromi Arai, Sébastien Gambs, Satoshi Hara

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning-based Incast Performance Inference in Software-Defined Data Centers.

Kokouvi Bénoît Nougnanke, Yann Labit, Marc Bruyere, Simone Ferlin, Ulrich Aïvodji

Proceedings of the 24th Conference on Innovation in Clouds, 2021

FairCORELS, an Open-Source Library for Learning Fair Rule Lists.

Ulrich Aïvodji, Julien Ferry, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Privacy in trajectory micro-data publishing: a survey.

Marco Fiore, Panagiota Katsikouli, Elli Zavou, Mathieu Cunche, Françoise Fessant, Dominique Le Hello, Ulrich Matchi Aïvodji, Baptiste Olivier, Tony Quertier, Razvan Stanica

Trans. Data Priv., 2020

Model extraction from counterfactual explanations.

Ulrich Aïvodji, Alexandre Bolot, Sébastien Gambs

CoRR, 2020

2019

GAMIN: An Adversarial Approach to Black-Box Model Inversion.

Ulrich Aïvodji, Sébastien Gambs, Timon Ther

CoRR, 2019

Learning Fair Rule Lists.

Ulrich Aïvodji, Julien Ferry, Sébastien Gambs, Marie-José Huguet, Mohamed Siala

CoRR, 2019

Agnostic data debiasing through a local sanitizer learnt from an adversarial network approach.

Ulrich Aïvodji, François Bidet, Sébastien Gambs, Rosin Claude Ngueveu, Alain Tapp

CoRR, 2019

Privacy of trajectory micro-data : a survey.

Marco Fiore, Panagiota Katsikouli, Elli Zavou, Mathieu Cunche, Françoise Fessant, Dominique Le Hello, Ulrich Matchi Aïvodji, Baptiste Olivier, Tony Quertier, Razvan Stanica

CoRR, 2019

IOTFLA : A Secured and Privacy-Preserving Smart Home Architecture Implementing Federated Learning.

Ulrich Matchi Aïvodji, Sébastien Gambs, Alexandre Martin

Proceedings of the 2019 IEEE Security and Privacy Workshops, 2019

Fairwashing: the risk of rationalization.

Ulrich Aïvodji, Hiromi Arai, Olivier Fortineau, Sébastien Gambs, Satoshi Hara, Alain Tapp

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Privacy-Enhancing Technologies for Ridesharing. (Technologies respectueuses de la vie privée pour le covoiturage).

Ulrich Aïvodji

PhD thesis, 2018

SRide: A Privacy-Preserving Ridesharing System.

Ulrich Matchi Aïvodji, Kévin Huguenin, Marie-José Huguet, Marc-Olivier Killijian

Proceedings of the 11th ACM Conference on Security & Privacy in Wireless and Mobile Networks, 2018