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Miriam Rateike
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2020 – today
- 2024
- [c5]Miriam Rateike
, Isabel Valera
, Patrick Forré
:
Designing Long-term Group Fair Policies in Dynamical Systems. FAccT 2024: 20-50 - 2023
- [i4]Miriam Rateike, Isabel Valera, Patrick Forré:
Designing Long-term Group Fair Policies in Dynamical Systems. CoRR abs/2311.12447 (2023) - [i3]Miriam Rateike, Celia Cintas, John Wamburu, Tanya Akumu, Skyler Speakman:
Weakly Supervised Detection of Hallucinations in LLM Activations. CoRR abs/2312.02798 (2023) - 2022
- [c4]Pablo Sánchez-Martín, Miriam Rateike, Isabel Valera:
VACA: Designing Variational Graph Autoencoders for Causal Queries. AAAI 2022: 8159-8168 - [c3]Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt J. Kusner, Jessica Schrouff:
Algorithmic Fairness through the Lens of Causality and Privacy (AFCP) 2022. AFCP 2022: 1-6 - [c2]Miriam Rateike, Ayan Majumdar
, Olga Mineeva, Krishna P. Gummadi
, Isabel Valera
:
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making. FAccT 2022: 1421-1433 - [e2]Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt J. Kusner, Jessica Schrouff:
Algorithmic Fairness through the Lens of Causality and Privacy Workshop, AFCP 2022, New Orleans, LA, USA (hybrid), 03 December 2022. Proceedings of Machine Learning Research 214, PMLR 2022 [contents] - [i2]Miriam Rateike, Ayan Majumdar, Olga Mineeva, Krishna P. Gummadi
, Isabel Valera:
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making. CoRR abs/2205.04790 (2022) - 2021
- [c1]Jessica Schrouff, Awa Dieng, Miriam Rateike, Kweku Kwegyir-Aggrey, Golnoosh Farnadi:
Algorithmic Fairness through the Lens of Causality and Robustness (AFCR) 2021. AFCR 2021: 1-5 - [e1]Jessica Schrouff, Awa Dieng, Miriam Rateike, Kweku Kwegyir-Aggrey, Golnoosh Farnadi:
Algorithmic Fairness through the Lens of Causality and Robustness Workshop, AFCR 2021, virtual, December 13, 2021. Proceedings of Machine Learning Research 171, PMLR 2021 [contents] - [i1]Pablo Sánchez-Martín, Miriam Rateike, Isabel Valera:
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries. CoRR abs/2110.14690 (2021)
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