Bayesian Models and Algorithms for Fairness and Transparency

Project Information

BayesianGDPR

Grant agreement ID: 851538

DOI

10.3030/851538

Project closed

EC signature date 28 January 2020

Start date 1 April 2020

End date 30 September 2025

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 443 697,00

EU contribution

€ 1 443 697,00

Coordinated by

THE UNIVERSITY OF SUSSEX
United Kingdom

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Peer reviewed articles (5)

Preserving the Fairness Guarantees of Classifiers in Changing Environments: a Survey

Author(s): Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano, Novi Quadrianto
Published in: ACM Computing Surveys, 2023, ISSN 0360-0300
Publisher: Association for Computing Machinary, Inc.
DOI: 10.1145/3637438

Addressing Attribute Bias with Adversarial Support-Matching

Author(s): Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto
Published in: Transactions on Machine Learning Research, 2024, ISSN 2835-8856
Publisher: OpenReview
DOI: 10.48550/arxiv.2203.13154

Privacy and Accuracy Implications of Model Complexity and Integration in Heterogeneous Federated Learning

Author(s): Gergely D. Németh, Miguel Ángel Lozano, Novi Quadrianto, Nuria Oliver
Published in: IEEE Access, Issue 13, 2025, Page(s) 40258-40274, ISSN 2169-3536
Publisher: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2025.3546478

A Snapshot of the Frontiers of Client Selection in Federated Learning

Author(s): Gergely Dániel Németh, Miguel Ángel Lozano, Novi Quadrianto, Nuria Oliver
Published in: Transactions on Machine Learning Research, 2022, ISSN 2835-8856
Publisher: OpenReview
DOI: 10.48550/arxiv.2210.04607

Causal Datasheet for Datasets: An Evaluation Guide for Real-World Data Analysis and Data Collection Design Using Bayesian Networks

Author(s): Bradley Butcher, Vincent S. Huang, Christopher Robinson, Jeremy Reffin, Sema K. Sgaier, Grace Charles, Novi Quadrianto
Published in: Frontiers in Artificial Intelligence, Issue 4, 2021, ISSN 2624-8212
Publisher: [Lausanne]: Frontiers Media S.A., [2018]-
DOI: 10.3389/frai.2021.612551

Other (3)

Addressing Membership Inference Attack in Federated Learning with Model Compression

Author(s): Gergely Dániel Németh, Miguel Ángel Lozan, Novi Quadrianto, Nuria Oliver
Published in: 2023
Publisher: arXiv

The Decoupled Risk Landscape in Performative Prediction

Author(s): Javier Sanguino, Thomas Kehrenberg, José Antonio Lozano, Novi Quadrianto
Published in: 2025
Publisher: arXiv
DOI: 10.48550/arxiv.2506.09044

Contrastive Examples for Addressing the Tyranny of the Majority

Author(s): Sharmanska, Viktoriia; Hendricks, Lisa Anne; Darrell, Trevor; Quadrianto, Novi
Published in: Issue 1, 2020
Publisher: N/A

Conference proceedings (9)

Are Compressed Language Models Less Subgroup Robust?

Author(s): Leonidas Gee, Andrea Zugarini, Novi Quadrianto
Published in: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023, Page(s) 15859-15868
Publisher: Association for Computational Linguistics
DOI: 10.18653/v1/2023.emnlp-main.983

Racial Disparities in the Enforcement of Marijuana Violations in the US

Author(s): Butcher, Bradley; Robinson, Chris; Zilka, Miri; Fogliato, Riccardo; Ashurst, Carolyn; Weller, Adrian
Published in: AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 2022, ISBN 9781450392471
Publisher: Association for Computing Machinery
DOI: 10.1145/3514094.3534184

RealPatch: A Statistical Matching Framework for Model Patching with Real Samples

Author(s): Sara Romiti, Christopher Inskip, Viktoriia Sharmanska, Novi Quadrianto
Published in: Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXV, 2022, Page(s) 146–162, ISBN 978-3-031-19805-2
Publisher: Springer-Verlag
DOI: 10.1007/978-3-031-19806-9_9

FedDiverse: Tackling Data Heterogeneity in Federated Learning with Diversity-Driven Client Selection

Author(s): Gergely D. Németh, Eros Fanì, Yeat Jeng Ng, Barbara Caputo, Miguel Ángel Lozano, Nuria Oliver, Novi Quadrianto
Published in: The 3rd International Conference on Federated Learning Technologies and Applications, 2025
Publisher: IEEE

Null-Sampling for Interpretable and Fair Representations

Author(s): Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, Novi Quadrianto
Published in: Computer Vision – ECCV 2020 - 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXVI, 2020, Page(s) 565-580, ISBN 978-3-030-58573-0
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-58574-7_34

Okapi: Generalising Better by Making Statistical Matches Match

Author(s): Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto
Published in: Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022
Publisher: Curran Associates, Inc.

An Algorithmic Framework for Positive Action

Author(s): Oliver Thomas, Miri Zilka, Adrian Weller, Novi Quadrianto
Published in: Equity and Access in Algorithms, Mechanisms, and Optimization, 2021, Page(s) 1-13, ISBN 9781450385534
Publisher: ACM
DOI: 10.1145/3465416.3483303

Disagreement-based Active Learning for Robustness Against Subpopulation Shifts

Author(s): Yeat Jeng Ng, Viktoriia Sharmanska, Thomas Kehrenberg, Anastasia Pentina, Novi Quadrianto
Published in: Communications in Computer and Information Science, 2024
Publisher: Springer Nature

Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results

Author(s): Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano, Novi Quadrianto
Published in: International Conference on Artificial Intelligence and Statistics, 2024
Publisher: Proceedings of Machine Learning Research
DOI: 10.48550/arxiv.2302.01079

Thesis and dissertations (5)

Semi-supervised methods for distributionally-robust learning

Author(s): Myles Bartlett
Published in: 2023
Publisher: N/A

Fair Representations in the Data Domain

Author(s): Oliver Thomas
Published in: 2022
Publisher: N/A

Towards generalisation in machine learning under subpopulation shifts: active, passive, and spectral bias perspectives

Author(s): Yeat Jeng Ng
Published in: 2025
Publisher: University of Sussex

Statistical Matching for Vision Tasks: Mitigating Spurious Correlations and Out-Of-Distribution Generalization

Author(s): Sara Romiti
Published in: 2023
Publisher: N/A

Relaxing Core Assumptions: the Impact of Data, Model and Participation Heterogeneity on Performance, Privacy and Fairness in Federated Learning

Author(s): Gergely Dániel Németh
Published in: 2025
Publisher: University of Alicante