Conference Proceedings

  • Minimax Demographic Group Fairness in Federated Learning
    Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel Rodrigues
    2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT 2022) [Paper] [Code]

  • Blind Pareto Fairness and Subgroup Robustness
    Natalia Martinez, Martin Bertran, Afroditi Papadaki, Miguel Rodrigues, Guillermo Sapiro
    Proceedings of the 38th International Conference on Machine Learning (ICML 2021) [Paper] [Code]

  • Adversarially Learned Representations for Information Obfuscation and Inference
    Martin Bertran, Natalia Martinez, Afroditi Papadaki, Qiang Qiu, Miguel Rodrigues, Galen Reeves, Guillermo Sapiro
    36th International Conference on Machine Learning, (ICML 2019) [Paper] [Code]

Workshops

  • Federated Fairness without Access to Demographics
    Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel Rodrigues
    Workshop on Federated Learning: Recent Advances and New Challenges (in Conjunction with NeurIPS 2022) [Paper]

  • Federating for Learning Group Fair Models
    Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel Rodrigues
    New Frontiers in Federated Learning: Privacy, Fairness, Robustness, Personalization and Data Ownership at the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) [Paper]

  • Pareto Robustness for Fairness Beyond Demographics
    Natalia Martinez, Martin Bertran, Afroditi Papadaki, Miguel Rodrigues, Guillermo Sapiro
    Fair AI in Finance at the 34th Conference on Neural Information Processing Systems (NeurIPS 2020) [Video]

  • Learning Representations for Utility and Privacy: An Information-Theoretic Based Approach
    Martin Bertran, Natalia Martinez, Afroditi Papadaki, Qiang Qiu, Miguel Rodrigues, Guillermo Sapiro
    Privacy Preserving Machine Learning at the 30th Conference on Neural Information Processing Systems (NeurIPS 2018) [Paper]

  • Learning and Deciding Our Own Privacy in a Collaborative System
    Martin Bertran, Natalia Martinez, Afroditi Papadaki, Qiang Qiu, Miguel Rodrigues, Guillermo Sapiro
    Privacy in Machine Learning and Artificial Intelligence at the 35th International Conference on Machine Learning (ICML 2018)

Manuscripts

  • Federated Fairness without Access to Sensitive Groups
    Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel Rodrigues
    arXiv preprint, 2024 [Paper]

  • Learning to Collaborate for User-Controlled Privacy
    Martin Bertran, Natalia Martinez, Afroditi Papadaki, Qiang Qiu, Miguel Rodrigues and Guillermo Sapiro
    arXiv preprint, 2018 [Paper]