Bayesian Models and Algorithms for Fairness and Transparency

Información del proyecto

BayesianGDPR

Identificador del acuerdo de subvención: 851538

DOI

10.3030/851538

Proyecto cerrado

Fecha de la firma de la CE 28 Enero 2020

Fecha de inicio 1 Abril 2020

Fecha de finalización 30 Septiembre 2025

Financiado con arreglo a

• EXCELLENT SCIENCE - European Research Council (ERC)

Coste total

€ 1 443 697,00

Aportación de la UE

€ 1 443 697,00

Coordinado por

THE UNIVERSITY OF SUSSEX
United Kingdom

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Publicaciones

Peer reviewed articles (5)

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

Autores: Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano, Novi Quadrianto
Publicado en: ACM Computing Surveys, 2023, ISSN 0360-0300
Editor: Association for Computing Machinary, Inc.
DOI: 10.1145/3637438

Addressing Attribute Bias with Adversarial Support-Matching

Autores: Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto
Publicado en: Transactions on Machine Learning Research, 2024, ISSN 2835-8856
Editor: OpenReview
DOI: 10.48550/arxiv.2203.13154

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

Autores: Gergely D. Németh, Miguel Ángel Lozano, Novi Quadrianto, Nuria Oliver
Publicado en: IEEE Access, Edición 13, 2025, Página(s) 40258-40274, ISSN 2169-3536
Editor: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2025.3546478

A Snapshot of the Frontiers of Client Selection in Federated Learning

Autores: Gergely Dániel Németh, Miguel Ángel Lozano, Novi Quadrianto, Nuria Oliver
Publicado en: Transactions on Machine Learning Research, 2022, ISSN 2835-8856
Editor: 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

Autores: Bradley Butcher, Vincent S. Huang, Christopher Robinson, Jeremy Reffin, Sema K. Sgaier, Grace Charles, Novi Quadrianto
Publicado en: Frontiers in Artificial Intelligence, Edición 4, 2021, ISSN 2624-8212
Editor: [Lausanne]: Frontiers Media S.A., [2018]-
DOI: 10.3389/frai.2021.612551

Other (3)

Addressing Membership Inference Attack in Federated Learning with Model Compression

Autores: Gergely Dániel Németh, Miguel Ángel Lozan, Novi Quadrianto, Nuria Oliver
Publicado en: 2023
Editor: arXiv

The Decoupled Risk Landscape in Performative Prediction

Autores: Javier Sanguino, Thomas Kehrenberg, José Antonio Lozano, Novi Quadrianto
Publicado en: 2025
Editor: arXiv
DOI: 10.48550/arxiv.2506.09044

Contrastive Examples for Addressing the Tyranny of the Majority

Autores: Sharmanska, Viktoriia; Hendricks, Lisa Anne; Darrell, Trevor; Quadrianto, Novi
Publicado en: Edición 1, 2020
Editor: N/A

Conference proceedings (9)

Are Compressed Language Models Less Subgroup Robust?

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

Racial Disparities in the Enforcement of Marijuana Violations in the US

Autores: Butcher, Bradley; Robinson, Chris; Zilka, Miri; Fogliato, Riccardo; Ashurst, Carolyn; Weller, Adrian
Publicado en: AIES '22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 2022, ISBN 9781450392471
Editor: Association for Computing Machinery
DOI: 10.1145/3514094.3534184

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

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

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

Autores: Gergely D. Németh, Eros Fanì, Yeat Jeng Ng, Barbara Caputo, Miguel Ángel Lozano, Nuria Oliver, Novi Quadrianto
Publicado en: The 3rd International Conference on Federated Learning Technologies and Applications, 2025
Editor: IEEE

Null-Sampling for Interpretable and Fair Representations

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

Okapi: Generalising Better by Making Statistical Matches Match

Autores: Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto
Publicado en: Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022
Editor: Curran Associates, Inc.

An Algorithmic Framework for Positive Action

Autores: Oliver Thomas, Miri Zilka, Adrian Weller, Novi Quadrianto
Publicado en: Equity and Access in Algorithms, Mechanisms, and Optimization, 2021, Página(s) 1-13, ISBN 9781450385534
Editor: ACM
DOI: 10.1145/3465416.3483303

Disagreement-based Active Learning for Robustness Against Subpopulation Shifts

Autores: Yeat Jeng Ng, Viktoriia Sharmanska, Thomas Kehrenberg, Anastasia Pentina, Novi Quadrianto
Publicado en: Communications in Computer and Information Science, 2024
Editor: Springer Nature

Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results

Autores: Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano, Novi Quadrianto
Publicado en: International Conference on Artificial Intelligence and Statistics, 2024
Editor: Proceedings of Machine Learning Research
DOI: 10.48550/arxiv.2302.01079

Thesis and dissertations (5)

Semi-supervised methods for distributionally-robust learning

Autores: Myles Bartlett
Publicado en: 2023
Editor: N/A

Fair Representations in the Data Domain

Autores: Oliver Thomas
Publicado en: 2022
Editor: N/A

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

Autores: Yeat Jeng Ng
Publicado en: 2025
Editor: University of Sussex

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

Autores: Sara Romiti
Publicado en: 2023
Editor: N/A

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

Autores: Gergely Dániel Németh
Publicado en: 2025
Editor: University of Alicante