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Paper Citation Record · LEDGER

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics

As of 18 August 2026, this Paper Citation Record lists 100 of 227 outbound references and 0 inbound Pith citation observations for arXiv:2411.09056.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.09056 v1

Coverage vector

measured 100 of 227 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:11:25.316893Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

100 of 227 outbound references displayed

  • verified exact1
  • verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c998f163-0620-4fd5-8266-6b90de632c12 · outbound

This paper cites and Mare c ek, J.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Mare c ek, J

Reference 1

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Observation e957db76-af37-4dbd-b5ab-107d315d80a6 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 2

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Observation f3a6b694-af10-415c-9831-5b30a01c9bc8 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 3

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 4

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This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 5

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Observation 073fc8cd-0702-419f-88f3-1eb8f74a3b9e · outbound

This paper cites J., and Vayanos, P.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics J., and Vayanos, P

Reference 6

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Carlier, G

Reference 7

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 8

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Observation 77fa9fd8-9fbe-4883-8c39-a785e835028c · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 9

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This paper cites P., Schwarting, W., Bhatia, S.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics P., Schwarting, W., Bhatia, S

Reference 10

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 11

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 12

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Villeneuve, S

Reference 13

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 14

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Weller, A

Reference 15

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics B., Brevoort, K

Reference 16

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Observation 929c0b13-4cc9-4965-832b-c0dbefc81476 · outbound

This paper cites Beyond Individual and Group Fairness.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Beyond Individual and Group Fairness

Reference 17

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Reference 18

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Observation d16987eb-75d0-4fa3-b4f6-1b4b2ddb5e38 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics A New Approach to Learning Linear Dynamical Systems

Reference 19

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 20

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Selbst, A

Reference 21

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics H., Burachik, R

Reference 22

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Reference 23

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Kohavi, R

Reference 24

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics J., Hammel, E

Reference 29

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?

Reference 31

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Quantum open system identification via global optimization: Optimally accurate Markovian models of open systems from time-series data

Reference 33

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics (October 12th, 2023)

Reference 35

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and De Bie, T

Reference 38

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Observation c9a2b914-b3bc-4f82-aa00-d53082440629 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Z liobait \.e , I

Reference 40

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Observation 78cc401f-4c20-4e22-884d-c394deb037b7 · outbound

This paper cites P., Wei, D., Vinzamuri, B., Ramamurthy, K.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics P., Wei, D., Vinzamuri, B., Ramamurthy, K

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source=arxiv_source observed=2026-08-12T21:11:25.096958Z digest=sha256:ca8dd8e26dcbe73a04011468734a149cd4aa2bece402b3de2b7bb212f2ff23a5

Observation d9837180-8c2d-45de-8404-652a3814a7c1 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 42

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source=arxiv_source observed=2026-08-12T21:11:25.100790Z digest=sha256:a3c476f94c7ea18b7350061214e591ad68842a795acff829d596fd8bcdd247a9

Observation a3007444-c086-42ed-acb5-ceeb174509b8 · outbound

This paper cites and Haas, C.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Haas, C

Reference 43

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source=arxiv_source observed=2026-08-12T21:11:25.104326Z digest=sha256:d63f8b6931fca9a38c18d8496cddd77169b42d45b5ea269b3a906549b3b484be

Observation b6e3acff-b3b4-4774-b18f-f30eddd10a06 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 44

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source=arxiv_source observed=2026-08-12T21:11:25.108864Z digest=sha256:66794458e5ebaa14eb94fd273560e13fd20689ce6f200299eb0855d11042dab1

Observation d04ed490-da71-47a0-b80e-5b278cdea5f3 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 45

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source=arxiv_source observed=2026-08-12T21:11:25.112584Z digest=sha256:dc9b47b2f6448bca9d6b0c8b494899c46824a95a3cc30fd902a86e4f27621ac8

Observation 851f10c8-1379-441b-8cd6-93b8c5e17f1a · outbound

This paper cites and Wang, X.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Wang, X

Reference 46

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source=arxiv_source observed=2026-08-12T21:11:25.116495Z digest=sha256:77c08413c60f6a0b6dbba65f7ace12dc95b917ef1ecf3fe8e63630a5c7f90ff1

Observation 4686d127-d127-4af0-9dc0-9382c46112c2 · outbound

This paper cites and Shokri, R.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Shokri, R

Reference 47

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source=arxiv_source observed=2026-08-12T21:11:25.120256Z digest=sha256:7f568037013e228c1f0f73ddcf525792f15ebd1e82e9a4ba31f6b00da20607ac

Observation 9cb8b899-a9b5-4d5d-b0d1-722f9d8f7999 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 48

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source=arxiv_source observed=2026-08-12T21:11:25.123684Z digest=sha256:c44168a033e7fa0c55a6e204fb89850a21be93425fbd27f5a106138394e1c3d8

Observation 875e3419-e198-4731-b1f3-e42c5e3d1580 · outbound

This paper cites D., and Sontag, D.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics D., and Sontag, D

Reference 49

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source=arxiv_source observed=2026-08-12T21:11:25.127777Z digest=sha256:559d57bf3afc51f8a2a25e7604fdf2678f20287b94bd5c5c827ce54351199dc2

Observation 9cbee9c3-899d-4faa-976b-ab9f0f7d1251 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 50

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source=arxiv_source observed=2026-08-12T21:11:25.131906Z digest=sha256:65d1e75ce3cefb9016588140b51a074bdca3218455936d1161911da9dbe90f1d

Observation 00685319-80d8-4a19-ac94-6e1215d7c72e · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 51

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source=arxiv_source observed=2026-08-12T21:11:25.135591Z digest=sha256:2b2e486b93057b95d80dfbd907f96e858d37286ae84c0314e7d349faeeb2ba7a

Observation 5a587e68-b228-4d0b-b70d-2f1b3482bc7f · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 52

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source=arxiv_source observed=2026-08-12T21:11:25.139807Z digest=sha256:17dfeedf640bf2469e53f0df28b3783540cf7e5ebfc5ef26d4b30fc3648268c7

Observation a757ca3d-8549-43ff-93d5-00cec562e903 · outbound

This paper cites and Voit, E.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Voit, E

Reference 53

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source=arxiv_source observed=2026-08-12T21:11:25.144027Z digest=sha256:2df1c155d4ca597981d2cd63ce84efbfbaf11e377e18701b74f6e2bb66da13dd

Observation e1852acb-6522-417b-b81c-71324232e373 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 54

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source=arxiv_source observed=2026-08-12T21:11:25.147315Z digest=sha256:645326e8044a1daa30b8c858ef2e0f75f8028878824b0c916b67fe8fdb32f14e

Observation d0c29c47-395f-43fe-94d7-37ca48151da2 · outbound

This paper cites and Roth, A.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Roth, A

Reference 55

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source=arxiv_source observed=2026-08-12T21:11:25.151215Z digest=sha256:648993e1b492b4a68f7e76968d228a2b31a4ccdd9fb8b5088559cc7fe2a43d71

Observation 50d04b2e-752d-46ba-a5e1-6b43a266b2fb · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 56

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source=arxiv_source observed=2026-08-12T21:11:25.154305Z digest=sha256:7d35b2b4648574a48134a814efa57646ad4fd0f310c54bb569ddbb5c6aa74077

Observation 25f7c128-2646-4112-ad92-b74bae4f0662 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 57

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source=arxiv_source observed=2026-08-12T21:11:25.157594Z digest=sha256:4ab83d57e3e8c138998634c7261f71c688c1138761f88e1eb2a8432245e6962b

Observation 689428dc-67cf-404a-84a4-d1d381552e83 · outbound

This paper cites W., Biancofiore, G.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics W., Biancofiore, G

Reference 58

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source=arxiv_source observed=2026-08-12T21:11:25.161200Z digest=sha256:d9396a1b5c3c7f381dac51a8a1f7a049da07a2745cae057b041808e1d1b305af

Observation 06f02dda-fc54-4d31-8680-ee346ad6c1ff · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 59

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source=arxiv_source observed=2026-08-12T21:11:25.165365Z digest=sha256:270a68617055e58a7a47819f9be47e958bdbcc37d1ac2509d3976313b9937e7f

Observation 3b7529e9-4bc9-43bf-b8c5-0f88489c9548 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 60

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source=arxiv_source observed=2026-08-12T21:11:25.169045Z digest=sha256:bc10fbc8e1ba7dc3abf389cb720c63c47560c55da5ef77fcb442308813324763

Observation 2b9e0196-f5cb-4765-b67a-a9505563c9ad · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 61

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source=arxiv_source observed=2026-08-12T21:11:25.173852Z digest=sha256:777c3f0bd888dda520b0820daa2619d73054c75726fb47820afaf306599a0d82

Observation 67b1e2fa-cd02-47e3-91f6-d16487489981 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 62

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source=arxiv_source observed=2026-08-12T21:11:25.177828Z digest=sha256:14cf0fd15673162316470cd3c2bb06716ac054560f4c3eb4f4bb31f8a15b3c77

Observation 66a5524e-b90a-4c7d-b134-63be54f8815b · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 63

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source=arxiv_source observed=2026-08-12T21:11:25.181792Z digest=sha256:e7bf5e8af14c923da98c0397ae5ac6a064fa5ab39d9ee0c1e515f81b9e9ce29f

Observation 29aa397b-f8af-4d4f-9364-303b7d14fa56 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 64

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source=arxiv_source observed=2026-08-12T21:11:25.185332Z digest=sha256:f7d4377b0a017d314e029f00585d84b36d3f932385730bf8e00fb92bdaab7e11

Observation 3f0e82ba-3aaa-4d96-8a1f-ac19db21ec13 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 65

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source=arxiv_source observed=2026-08-12T21:11:25.188951Z digest=sha256:372c84d26a6e8453b459c93448b5b578e955a2d2dc92ca7881539abfdd363750

Observation 1248e0b5-0349-4f34-a16e-067db5b49957 · outbound

This paper cites and Farid, H.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Farid, H

Reference 66

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source=arxiv_source observed=2026-08-12T21:11:25.192838Z digest=sha256:7677ec2890316c4d2f26240b91a0e294927c03202ce09915f838e3fd930930ae

Observation 23c5c1bf-2c68-42b0-b594-b1b1a094ef5d · outbound

This paper cites Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing

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local_arxiv, observed 2026-08-12T21:11:25.919719Z

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source=arxiv_source observed=2026-08-12T21:11:25.196153Z digest=sha256:8f256fe66838333efc9b891bbc94628dde4bf88075d08173efc8b0acbbbbe1fc

Observation b44451c8-9a86-487f-9029-edc4f3da9f14 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 68

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source=arxiv_source observed=2026-08-12T21:11:25.200477Z digest=sha256:628479d268b822178f3de641864e8aeb6019508804f81acc66488de7e228e3a4

Observation 95abc419-279b-4357-8f7b-a13d2780b7d7 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 69

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source=arxiv_source observed=2026-08-12T21:11:25.205024Z digest=sha256:9118179d477107341ac1bf360ad5b24b15e42a62e45d862e987d5858a6012b07

Observation 723a480f-06ec-4560-aa68-83c8388b1282 · outbound

This paper cites and Temam, R.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Temam, R

Reference 70

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source=arxiv_source observed=2026-08-12T21:11:25.208616Z digest=sha256:e7fe0e944eb96fd5adfad1e541fd6882fe881f845e6033c0fc015851762d4120

Observation de826595-4144-46d1-af51-1f95dc8aa93a · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 71

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source=arxiv_source observed=2026-08-12T21:11:25.212119Z digest=sha256:8ca22e9ca4ff88fee4f0972dbd406fc61eeaf31676ef704edf026c4a1397a654

Observation aeadfa6b-fc2f-4dad-9579-83cd64ecf073 · outbound

This paper cites A., Neville, S., Scheidegger, C., and Venkatasubramanian, S.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics A., Neville, S., Scheidegger, C., and Venkatasubramanian, S

Reference 72

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source=arxiv_source observed=2026-08-12T21:11:25.215687Z digest=sha256:f083773e39cb942ebc62a8f97478cb642da93c2da29079a2038b2dd381a14088

Observation fac15a9c-46a7-4d9a-a64f-f7a324bc4321 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 73

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source=arxiv_source observed=2026-08-12T21:11:25.219909Z digest=sha256:0d4a9776b79165cbfb246ac432cdec075de3b76627cd24d7788044b74a664816

Observation 96e7cc37-c58e-4d78-ae60-2c5690f89e21 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 74

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source=arxiv_source observed=2026-08-12T21:11:25.223954Z digest=sha256:f135a55895f10e2c31d2815b034d2156090367d079131f6bf94ea9a16b8514dd

Observation 6798aa6a-e23e-4dff-bce2-3f3382ec628c · outbound

This paper cites A., Moeller, J., Scheidegger, C., and Venkatasubramanian, S.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics A., Moeller, J., Scheidegger, C., and Venkatasubramanian, S

Reference 75

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source=arxiv_source observed=2026-08-12T21:11:25.228615Z digest=sha256:c041529f31fcded0426fff728abdfecbe6106d28f26f2df0187639bdafd8b9b2

Observation 44faede3-2127-43b8-9efb-5836c7b2798c · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 76

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source=arxiv_source observed=2026-08-12T21:11:25.232397Z digest=sha256:2503de820a6a45e0b8ead0b00f7da3d869769eb7129da38156a21fc8f36caa8e

Observation f3b8f587-f1e8-4ada-ad2e-9834302211d9 · outbound

This paper cites M., Cot \'e , M., and Criado, N.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics M., Cot \'e , M., and Criado, N

Reference 77

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source=arxiv_source observed=2026-08-12T21:11:25.235895Z digest=sha256:561f7aa8d07ad630b99f20ca306d2fde0039d291b8bdb5e39798b5900179a102

Observation c6552589-2695-4445-b3ef-d1ee6ed8e69a · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 78

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source=arxiv_source observed=2026-08-12T21:11:25.239470Z digest=sha256:3d73be68f73df68f411daee80c23f9fc2a970c0ec9358163175a0aea5c6c7bf7

Observation 8c75f605-2a40-4c9d-b0ee-6e8bf6cf1828 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 79

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source=arxiv_source observed=2026-08-12T21:11:25.242842Z digest=sha256:680e5b68aa7a7cac6924b23c47dac608c60598be0ba0ad250babed522df32dfe

Observation 3a1a30bb-4a48-402f-bc7c-52ebe1c90305 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 80

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source=arxiv_source observed=2026-08-12T21:11:25.246372Z digest=sha256:dbc67ed9889fbf3de79fa265634e60b62c228b1e8a170d4832a8e21f78f23806

Observation e37c05f5-4dfd-4d88-9c85-a48951d748a7 · outbound

This paper cites and Pechenizkiy, M.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Pechenizkiy, M

Reference 81

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This paper cites and \'S wi e ch, A.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and \'S wi e ch, A

Reference 82

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Reference 83

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This paper cites and Neumark, M.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Neumark, M

Reference 84

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Observation c96ef4b9-9d61-4c7c-9c78-420e7e66e3a8 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 85

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Projection to Fairness in Statistical Learning

Reference 86

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics M., Rasch, M

Reference 87

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This paper cites B., Gummadi, K.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics B., Gummadi, K

Reference 88

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Observation c8e1e840-ec9a-4281-a591-c3ec56214eab · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 89

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This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 90

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 91

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This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 92

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Observation cecc34c4-e74c-4f38-ada6-630fcbe4aab4 · outbound

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Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 93

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Observation db0c2478-a8e7-456c-86c4-44437dbf2dc9 · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 94

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Observation 0f6943b3-6813-4c7a-ae22-639df099e10f · outbound

This paper cites and Ma, Y.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Ma, Y

Reference 95

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Observation 2e5afa17-e374-4a66-ad47-503cb34fe51c · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 96

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Observation 675c024f-1f5b-4b27-af8a-0f5309e3b3c0 · outbound

This paper cites and McCullough, S.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and McCullough, S

Reference 97

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Observation 6949b538-1705-4f3d-9467-840b9c16004b · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 98

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Observation 935da594-892d-48e4-aced-e1563f4fbcc8 · outbound

This paper cites and Zhang, L.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics and Zhang, L

Reference 99

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Observation e074f677-ca02-4d32-901e-faf0913c963e · outbound

This paper cites an unresolved cited work.

Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics Unresolved cited work

Reference 100

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Pith citing papers

No inbound Pith citation observations are available.