Paper Citation Record · LEDGER

Functional Bilevel Optimization for Predictive Fairness

As of 10 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.05098.

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pith.paper-citation-record.v1
2607.05098 v1

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measured 46 of 46 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-07-11T08:52:08.656117Z

measured 46 of 46 standing notices

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Reference resolution

46 of 46 outbound references displayed

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Outbound references

Observation 3b834bfa-00b1-4315-9723-05dcff67306b · outbound

This paper cites an unresolved cited work.

Functional Bilevel Optimization for Predictive Fairness Unresolved cited work

Reference 1

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Observation 98fabec2-b83a-4fd3-957b-43a9c5a7303d · outbound

This paper cites A survey on bias and fairness in machine learning.ACM Computing Surveys, 54:1–35, 2021.

Functional Bilevel Optimization for Predictive Fairness A survey on bias and fairness in machine learning.ACM Computing Surveys, 54:1–35, 2021

Reference 2

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Observation 7444b6c1-9e30-4191-a409-a85324940bf7 · outbound

This paper cites Generalized demographic parity for group fairness.International Conference on Learning Representations (ICLR), 2022.

Functional Bilevel Optimization for Predictive Fairness Generalized demographic parity for group fairness.International Conference on Learning Representations (ICLR), 2022

Reference 3

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Observation 7f516474-7faa-43d7-9c19-9ee012b63a55 · outbound

This paper cites Equality of opportunity in supervised learning.

Functional Bilevel Optimization for Predictive Fairness Equality of opportunity in supervised learning

Reference 4

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Observation 88ba9c5f-2f09-4405-807e-b7689dc7bdb1 · outbound

This paper cites Kusner, Joshua Loftus, Chris Russell, and Ricardo Silva.

Functional Bilevel Optimization for Predictive Fairness Kusner, Joshua Loftus, Chris Russell, and Ricardo Silva

Reference 5

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Observation c8c4c9ff-036e-494a-a050-6e7836d2f0f8 · outbound

This paper cites MIT Press, 2023.

Functional Bilevel Optimization for Predictive Fairness MIT Press, 2023

Reference 6

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Observation c5dd8f4f-d099-4558-9758-47d0bbbdba00 · outbound

This paper cites Fair prediction with disparate impact: A study of bias in recidivism prediction instruments.Big Data, 5(2):153–163, 2017.

Functional Bilevel Optimization for Predictive Fairness Fair prediction with disparate impact: A study of bias in recidivism prediction instruments.Big Data, 5(2):153–163, 2017

Reference 7

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Observation 4f4bdbc4-1c2b-4d66-9499-319c0c772b7c · outbound

This paper cites Inherent trade-offs in the fair determination of risk scores.

Functional Bilevel Optimization for Predictive Fairness Inherent trade-offs in the fair determination of risk scores

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 39640a53-cd72-4866-9d86-dc020817d2be · outbound

This paper cites Fairness-aware classifier with prejudice remover regularizer.Machine Learning and Knowledge Discovery in Databases, pages 35–50, 2012.

Functional Bilevel Optimization for Predictive Fairness Fairness-aware classifier with prejudice remover regularizer.Machine Learning and Knowledge Discovery in Databases, pages 35–50, 2012

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 355395c6-3a9b-44f1-8627-ab2ae78d9673 · outbound

This paper cites Teo, Le Song, Bernhard Schölkopf, and Alex J.

Functional Bilevel Optimization for Predictive Fairness Teo, Le Song, Bernhard Schölkopf, and Alex J

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation ae721534-ca39-49fe-8589-6ffab107acfe · outbound

This paper cites Mitigating unwanted biases with adversarial learning.Proceedings of the Conference on AI, Ethics, and Society (AIES), pages 335–340, 2018.

Functional Bilevel Optimization for Predictive Fairness Mitigating unwanted biases with adversarial learning.Proceedings of the Conference on AI, Ethics, and Society (AIES), pages 335–340, 2018

Reference 11

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Observation fb275d15-525f-41a5-a29f-0c2a6e8eddfb · outbound

This paper cites Censoring representations with an adversary.International Conference on Learning Representations (ICLR), 2016.

Functional Bilevel Optimization for Predictive Fairness Censoring representations with an adversary.International Conference on Learning Representations (ICLR), 2016

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 5a32b568-8a46-481f-bc22-d4d6cfcb442b · outbound

This paper cites Fairness-aware learning for continuous attributes and treatments.Proceedings of Machine Learning Research (PMLR), 97: 4382–4391, 2019.

Functional Bilevel Optimization for Predictive Fairness Fairness-aware learning for continuous attributes and treatments.Proceedings of Machine Learning Research (PMLR), 97: 4382–4391, 2019

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 235b1bfe-b43c-48da-b6c4-b1ce0a69b478 · outbound

This paper cites an unresolved cited work.

Functional Bilevel Optimization for Predictive Fairness Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 6b926f22-ea21-4a08-981d-2a7751cbd988 · outbound

This paper cites Fair Bilevel Neural Network (FairBiNN): On Balancing Fairness and Accuracy via Stackelberg Equilibrium.Advances in Neural Information Processing Systems (NeurIPS), 2024.

Functional Bilevel Optimization for Predictive Fairness Fair Bilevel Neural Network (FairBiNN): On Balancing Fairness and Accuracy via Stackelberg Equilibrium.Advances in Neural Information Processing Systems (NeurIPS), 2024

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation fe11d639-7385-4d8a-aed7-5965c1c113d1 · outbound

This paper cites Nonconvex optimization for regression with fairness constraints.

Functional Bilevel Optimization for Predictive Fairness Nonconvex optimization for regression with fairness constraints

Reference 16

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Observation e7ac085b-4e61-4f01-9565-d53787f4276e · outbound

This paper cites Mitigating discrimination in insurance with wasserstein barycenters.PKDD/ECML Workshops, 2023.

Functional Bilevel Optimization for Predictive Fairness Mitigating discrimination in insurance with wasserstein barycenters.PKDD/ECML Workshops, 2023

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 764458a7-d6e0-41fd-8027-1df603179bbc · outbound

This paper cites Should bank stress tests be fair?Management Science, 71(1): 262–278, 2024.

Functional Bilevel Optimization for Predictive Fairness Should bank stress tests be fair?Management Science, 71(1): 262–278, 2024

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-11T08:57:58.009229Z

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Observation 28349ae3-8381-4830-9e74-cef217fe0089 · outbound

This paper cites FairJob: A Real-World Dataset for Fairness in Online Systems.Advances in Neural Information Processing Systems (NeurIPS), 2024.

Functional Bilevel Optimization for Predictive Fairness FairJob: A Real-World Dataset for Fairness in Online Systems.Advances in Neural Information Processing Systems (NeurIPS), 2024

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation ae579c7b-0142-4267-9f3c-779638bf6025 · outbound

This paper cites Functional bilevel optimization for machine learning.Advances in Neural Information Processing Systems (NeurIPS), 2024.

Functional Bilevel Optimization for Predictive Fairness Functional bilevel optimization for machine learning.Advances in Neural Information Processing Systems (NeurIPS), 2024

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation d57d09ee-638b-48e1-8706-748e9e061b9e · outbound

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Functional Bilevel Optimization for Predictive Fairness Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation bdb25c89-0179-4fce-b68f-0fbac6da1395 · outbound

This paper cites A reductions approach to fair classification.Proceedings of Machine Learning Research (PMLR), 80:60–69, 2018.

Functional Bilevel Optimization for Predictive Fairness A reductions approach to fair classification.Proceedings of Machine Learning Research (PMLR), 80:60–69, 2018

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 638dc7ae-61fe-45f7-be92-74ff933c921a · outbound

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Functional Bilevel Optimization for Predictive Fairness Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation cc74c355-9e74-4efd-97fe-8c1735e25a49 · outbound

This paper cites Fair kernel learning.

Functional Bilevel Optimization for Predictive Fairness Fair kernel learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 77b04d72-945d-479b-b442-8d512ca58f8c · outbound

This paper cites Kernel dependence reg- ularizers and Gaussian processes with applications to algorithmic fairness.Pattern Recognition, 132:108922, 2022.

Functional Bilevel Optimization for Predictive Fairness Kernel dependence reg- ularizers and Gaussian processes with applications to algorithmic fairness.Pattern Recognition, 132:108922, 2022

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 6863828c-9851-4551-ae5b-f0a4c04f1e6c · outbound

This paper cites Fair regression with Wasserstein barycenters.

Functional Bilevel Optimization for Predictive Fairness Fair regression with Wasserstein barycenters

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 9136b022-79f4-4078-b090-3580f938276a · outbound

This paper cites Projection to Fairness in Statistical Learning.

Functional Bilevel Optimization for Predictive Fairness Projection to Fairness in Statistical Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 5405e527-5521-442c-91c5-11df9bf83dba · outbound

This paper cites A minimax framework for quantifying risk-fairness trade-off in regression.The Annals of Statistics, 50(4):2416–2442, 2022.

Functional Bilevel Optimization for Predictive Fairness A minimax framework for quantifying risk-fairness trade-off in regression.The Annals of Statistics, 50(4):2416–2442, 2022

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 78e9eb42-9f96-479a-a42a-abae68542003 · outbound

This paper cites Fair learning with Wasserstein barycenters for non-decomposable performance measures.International Conference on Artifi- cial Intelligence and Statistics (AISTATS), 2023.

Functional Bilevel Optimization for Predictive Fairness Fair learning with Wasserstein barycenters for non-decomposable performance measures.International Conference on Artifi- cial Intelligence and Statistics (AISTATS), 2023

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 5d639784-a209-4569-ba19-9973bb2417d4 · outbound

This paper cites Fairness-aware neural Rényi min- imization for continuous features.International Joint Conference on Artificial Intelligence (IJCAI), 2020.

Functional Bilevel Optimization for Predictive Fairness Fairness-aware neural Rényi min- imization for continuous features.International Joint Conference on Artificial Intelligence (IJCAI), 2020

Reference 30

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Observation 4c8cc136-1a3e-4733-b8de-26323b0ff13a · outbound

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Functional Bilevel Optimization for Predictive Fairness Unresolved cited work

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 02a446aa-4682-4824-a158-ba45d697295a · outbound

This paper cites Fairbatch: Batch selection for model fairness.International Conference on Learning Representations (ICLR), 2021.

Functional Bilevel Optimization for Predictive Fairness Fairbatch: Batch selection for model fairness.International Conference on Learning Representations (ICLR), 2021

Reference 32

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Observation 252f77ec-d756-46f4-8bdc-f5aa3236840e · outbound

This paper cites Fair machine learning under limited demographically labeled data.Workshop on Socially Responsible Machine Learning (SRML), 2022.

Functional Bilevel Optimization for Predictive Fairness Fair machine learning under limited demographically labeled data.Workshop on Socially Responsible Machine Learning (SRML), 2022

Reference 33

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Observation 0f267f9c-6d43-4db3-bc3f-96adda2dc946 · outbound

This paper cites Fairness-informed pareto optimization : An efficient bilevel framework.arXiv preprint arXiv:2601.13448, 2026.

Functional Bilevel Optimization for Predictive Fairness Fairness-informed pareto optimization : An efficient bilevel framework.arXiv preprint arXiv:2601.13448, 2026

Reference 34

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Observation bb1e007c-6b48-48a4-b9ed-d77d4a5b6ad2 · outbound

This paper cites Hyperparameter optimization with approximate gradient.Proceedings of Machine Learning Research (PMLR), 48:737–746, 2016.

Functional Bilevel Optimization for Predictive Fairness Hyperparameter optimization with approximate gradient.Proceedings of Machine Learning Research (PMLR), 48:737–746, 2016

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation 0ff89a63-8230-40fa-bf7c-ecc74499fe9a · outbound

This paper cites UCI machine learning repository, 2019.

Functional Bilevel Optimization for Predictive Fairness UCI machine learning repository, 2019

Reference 36

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Observation 4098d77e-12c5-4ea7-8d76-b3f567d7a8cf · outbound

This paper cites van Rijn, Bernd Bischl, and Luis Torgo.

Functional Bilevel Optimization for Predictive Fairness van Rijn, Bernd Bischl, and Luis Torgo

Reference 37

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Observation e24004fd-79b7-4efe-b511-4f5a4d40ef13 · outbound

This paper cites Mutual information neural estimation.Proceedings of Machine Learning Research (PMLR), 80:531–540, 2018.

Functional Bilevel Optimization for Predictive Fairness Mutual information neural estimation.Proceedings of Machine Learning Research (PMLR), 80:531–540, 2018

Reference 38

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Observation aaaf88f4-e92a-4adc-8973-31ca4e3fcdd9 · outbound

This paper cites Domain-adversarial training of neural networks.Journal of Machine Learning Research (JMLR), 17(59):1–35, 2016.

Functional Bilevel Optimization for Predictive Fairness Domain-adversarial training of neural networks.Journal of Machine Learning Research (JMLR), 17(59):1–35, 2016

Reference 39

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Observation 89f7b299-d095-4fe7-8098-e1f89e3d0bdc · outbound

This paper cites We work in L2(PAout) the space of square integrable functions wrt.

Functional Bilevel Optimization for Predictive Fairness We work in L2(PAout) the space of square integrable functions wrt

Reference 40

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Observation c39607c3-472d-49fb-b5f6-717ca737edc7 · outbound

This paper cites The adjointa ⋆ ω ∈L 2(PAin )solves ∂2 hhLin(ω, h⋆ ω)a⋆ ω =−∂ hLout(ω, h⋆ ω), hence 2a⋆ ω(a) =−2α(h ⋆ ω(a)−µ ω) a⋆ ω(a) =−α(h ⋆ ω(a)−µ ω), µ ω :=E A∼PAout [h⋆ ω(A)].

Functional Bilevel Optimization for Predictive Fairness The adjointa ⋆ ω ∈L 2(PAin )solves ∂2 hhLin(ω, h⋆ ω)a⋆ ω =−∂ hLout(ω, h⋆ ω), hence 2a⋆ ω(a) =−2α(h ⋆ ω(a)−µ ω) a⋆ ω(a) =−α(h ⋆ ω(a)−µ ω), µ ω :=E A∼PAout [h⋆ ω(A)]

Reference 41

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Observation 6c05ed5c-7a01-478e-963e-ebb7def772ed · outbound

This paper cites Compute each term •Direct outer term: ∂ωLout(ω, h⋆ ω) = 2E out [(fω(X)−Y)∂ ωfω(X)].

Functional Bilevel Optimization for Predictive Fairness Compute each term •Direct outer term: ∂ωLout(ω, h⋆ ω) = 2E out [(fω(X)−Y)∂ ωfω(X)]

Reference 42

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Observation 027d93be-cd14-4b3b-b4a0-4366ca6e1187 · outbound

This paper cites We compute cj =|corr(X j, y)| for every coordinate and rank coordinates in decreasing order ofc j.

Functional Bilevel Optimization for Predictive Fairness We compute cj =|corr(X j, y)| for every coordinate and rank coordinates in decreasing order ofc j

Reference 43

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Observation 49b55aea-2acd-4d1d-9a12-d4565d037a41 · outbound

This paper cites If this threshold leaves the pool empty, we fall back to the top-ranked coordinates without thresholding.

Functional Bilevel Optimization for Predictive Fairness If this threshold leaves the pool empty, we fall back to the top-ranked coordinates without thresholding

Reference 44

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Observation a9a3f848-dc05-46e0-965b-48fdd3074bde · outbound

This paper cites Concretely, we sample up to 128 other coordinates and define pj = max c̸=j |corr(Xc, Xj)|2, where the maximum is taken over the sampled coordinates.

Functional Bilevel Optimization for Predictive Fairness Concretely, we sample up to 128 other coordinates and define pj = max c̸=j |corr(Xc, Xj)|2, where the maximum is taken over the sampled coordinates

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-11T08:52:08.656117Z

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Observation c729fdd6-e31c-4362-91d3-82536f1b276a · outbound

This paper cites These selected coordinates are removed fromXbefore training the predictor.

Functional Bilevel Optimization for Predictive Fairness These selected coordinates are removed fromXbefore training the predictor

Reference 46

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