Fair machine learning through constrained stochastic optimization and an ϵ-constraint method
A strategy for fair supervised learning is proposed. It involves formulating an optimization problem to minimize loss subject to a prescribed bound on a measure of unfairness (e.g., disparate impact). It can be embedded within an ϵ -constraint method for multiobjective optimization, allowing one to...
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| Vydané v: | Optimization letters Ročník 18; číslo 9; s. 1975 - 1991 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.12.2024
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| ISSN: | 1862-4472, 1862-4480 |
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| Abstract | A strategy for fair supervised learning is proposed. It involves formulating an optimization problem to minimize loss subject to a prescribed bound on a measure of unfairness (e.g., disparate impact). It can be embedded within an
ϵ
-constraint method for multiobjective optimization, allowing one to produce a Pareto front for minimizing loss and unfairness. A stochastic optimization algorithm, designed to be scalable for large data settings, is proposed for solving the arising constrained optimization problems. Numerical experiments on problems pertaining to predicting recidivism and income provide evidence that the strategy can be effective for large-scale fair learning. |
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| AbstractList | A strategy for fair supervised learning is proposed. It involves formulating an optimization problem to minimize loss subject to a prescribed bound on a measure of unfairness (e.g., disparate impact). It can be embedded within an
ϵ
-constraint method for multiobjective optimization, allowing one to produce a Pareto front for minimizing loss and unfairness. A stochastic optimization algorithm, designed to be scalable for large data settings, is proposed for solving the arising constrained optimization problems. Numerical experiments on problems pertaining to predicting recidivism and income provide evidence that the strategy can be effective for large-scale fair learning. |
| Author | Curtis, Frank E. Liu, Suyun Robinson, Daniel P. |
| Author_xml | – sequence: 1 givenname: Frank E. orcidid: 0000-0001-7214-9187 surname: Curtis fullname: Curtis, Frank E. email: frank.e.curtis@lehigh.edu organization: Department of Industrial and Systems Engineering, Lehigh University – sequence: 2 givenname: Suyun surname: Liu fullname: Liu, Suyun organization: Department of Industrial and Systems Engineering, Lehigh University – sequence: 3 givenname: Daniel P. surname: Robinson fullname: Robinson, Daniel P. organization: Department of Industrial and Systems Engineering, Lehigh University |
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| Cites_doi | 10.1016/j.patcog.2007.10.009 10.1137/S1052623403426532 10.1002/nav.3800230402 10.1016/j.ejor.2018.05.064 10.1016/j.ejor.2007.12.014 10.1137/070702928 10.1109/TBIOM.2020.3027269 10.1137/20M1354556 10.1214/17-AOAS1058 10.1016/j.media.2016.05.011 10.1007/BF01588250 10.1146/annurev-statistics-042720-125902 10.1137/060672029 10.1007/s10618-010-0190-x 10.1016/j.ejor.2004.08.029 10.1007/s10115-021-01548-6 10.1109/TPAMI.2019.2901688 10.1007/s10107-008-0247-4 10.1016/j.media.2019.02.009 10.1002/mcda.1780 10.1016/j.neucom.2010.08.006 10.1137/16M1080173 10.1145/3194770.3194776 10.1007/978-3-319-46493-0_40 10.1109/ICDMW.2009.83 10.1007/BFb0067703 10.1109/ICCV.2019.01077 10.1109/CVPR.2019.01146 10.1007/s10479-021-04033-z 10.1109/ICASSP.2013.6639344 10.1109/CVPR42600.2020.00225 10.1007/978-3-642-33486-3_3 10.1007/978-3-540-74958-5_34 10.1177/0049124118782533 10.1109/ICASSP40776.2020.9054128 10.1109/CVPRW50498.2020.00369 10.1145/3038912.3052660 10.1007/978-3-030-06167-8_14 10.2139/ssrn.2477899 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| Copyright_xml | – notice: The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| References | Quentin, Fabrice, Désidéri (CR56) 2018; 271 Halffmann, Schäfer, Dächert, Klamroth, Ruzika (CR27) 2022; 29 Eichfelder (CR24) 2009; 19 CR39 CR38 CR37 Bachute, Subhedar (CR2) 2021; 6 CR35 CR34 CR33 CR32 CR75 Adeli, Li, Kwon, Zhang, Pohl (CR1) 2019; 42 CR30 CR74 CR71 Bolukbasi, Chang, Zou, Saligrama, Kalai (CR10) 2016; 29 Luedtke, Ahmed (CR48) 2008; 19 CR4 Berahas, Curtis, Robinson, Zhou (CR7) 2021; 31 CR3 CR6 CR5 CR8 Byrd, Gould, Nocedal, Waltz (CR12) 2004; 100 CR47 CR46 CR45 CR44 Cavazos, Phillips, Castillo, O’Toole (CR17) 2020; 3 CR43 Srinivasan, Thompson (CR59) 1976; 23 CR41 CR40 Luedtke, Ahmed, Nemhauser (CR49) 2010; 122 Bérubé, Gendreau, Potvin (CR9) 2009; 194 Zafar, Valera, Gomez-Rodriguez, Gummadi (CR70) 2019; 20 Calders, Verwer (CR16) 2010; 21 Han, Mangasarian (CR28) 1979; 17 Zhang, Chen, Zhou (CR72) 2008; 41 CR19 CR18 CR15 CR14 CR58 Mitchell, Potash, Barocas, D’Amour, Lum (CR52) 2021; 8 CR55 CR54 CR53 CR51 CR50 De Koninck, Nelissen, Baesens, Snoeck, De Weerdt (CR36) 2021; 63 Byrd, Gould, Nocedal, Waltz (CR13) 2006; 16 Laumanns, Thiele, Zitzler (CR42) 2006; 169 CR29 Zhang, Kwon, Pohl (CR73) 2017; 35 CR26 CR25 CR69 Bottou, Curtis, Nocedal (CR11) 2018; 60 Simoiu, Corbett-Davies, Goel (CR57) 2017; 11 CR68 CR23 CR22 Kervadec, Dolz, Tang, Granger, Boykov, Ayed (CR31) 2019; 54 CR66 CR21 CR65 CR20 CR64 CR63 CR62 CR61 CR60 Yang, Song (CR67) 2010; 73 T Calders (2024_CR16) 2010; 21 D Zhang (2024_CR72) 2008; 41 2024_CR53 2024_CR54 RH Byrd (2024_CR12) 2004; 100 2024_CR55 2024_CR50 2024_CR51 SP Han (2024_CR28) 1979; 17 2024_CR18 2024_CR19 2024_CR14 2024_CR58 2024_CR15 J Bérubé (2024_CR9) 2009; 194 James Luedtke (2024_CR49) 2010; 122 2024_CR43 2024_CR44 2024_CR45 2024_CR40 2024_CR41 James Luedtke (2024_CR48) 2008; 19 Mrinal R Bachute (2024_CR2) 2021; 6 JG Cavazos (2024_CR17) 2020; 3 2024_CR46 2024_CR47 C Simoiu (2024_CR57) 2017; 11 M Laumanns (2024_CR42) 2006; 169 MB Zafar (2024_CR70) 2019; 20 Léon Bottou (2024_CR11) 2018; 60 G Eichfelder (2024_CR24) 2009; 19 RH Byrd (2024_CR13) 2006; 16 Pascal Halffmann (2024_CR27) 2022; 29 2024_CR75 2024_CR32 2024_CR33 2024_CR34 M Yang (2024_CR67) 2010; 73 2024_CR71 2024_CR30 P De Koninck (2024_CR36) 2021; 63 2024_CR74 2024_CR39 M Quentin (2024_CR56) 2018; 271 2024_CR35 2024_CR37 2024_CR38 AS Berahas (2024_CR7) 2021; 31 T Bolukbasi (2024_CR10) 2016; 29 Y Zhang (2024_CR73) 2017; 35 2024_CR3 H Kervadec (2024_CR31) 2019; 54 2024_CR5 2024_CR4 2024_CR20 2024_CR64 2024_CR6 2024_CR21 2024_CR65 2024_CR22 2024_CR66 2024_CR8 2024_CR23 2024_CR60 2024_CR61 V Srinivasan (2024_CR59) 1976; 23 2024_CR62 2024_CR63 2024_CR29 2024_CR68 2024_CR25 2024_CR69 2024_CR26 S Mitchell (2024_CR52) 2021; 8 E Adeli (2024_CR1) 2019; 42 |
| References_xml | – ident: CR45 – ident: CR22 – ident: CR68 – volume: 41 start-page: 1440 year: 2008 end-page: 1451 ident: CR72 article-title: Constraint score: a new filter method for feature selection with pairwise constraints publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2007.10.009 – ident: CR74 – volume: 16 start-page: 471 issue: 2 year: 2006 end-page: 489 ident: CR13 article-title: On the convergence of successive linear-quadratic programming algorithms publication-title: SIAM J. Optim. doi: 10.1137/S1052623403426532 – volume: 23 start-page: 567 year: 1976 end-page: 595 ident: CR59 article-title: Algorithms for minimizing total cost, bottleneck time and bottleneck shipment in transportation problems publication-title: Nav. Res. Logist. Q. doi: 10.1002/nav.3800230402 – ident: CR4 – ident: CR39 – ident: CR51 – volume: 271 start-page: 808 year: 2018 end-page: 817 ident: CR56 article-title: A stochastic multiple gradient descent algorithm publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2018.05.064 – volume: 194 start-page: 39 year: 2009 end-page: 50 ident: CR9 article-title: An exact -constraint method for bi-objective combinatorial optimization problems: application to the traveling salesman problem with profits publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2007.12.014 – volume: 19 start-page: 674 issue: 2 year: 2008 end-page: 699 ident: CR48 article-title: A sample approximation approach for optimization with probabilistic constraints publication-title: SIAM J. Optim. doi: 10.1137/070702928 – ident: CR35 – ident: CR29 – ident: CR54 – ident: CR61 – volume: 3 start-page: 101 year: 2020 end-page: 111 ident: CR17 article-title: Accuracy comparison across face recognition algorithms: Where are we on measuring race bias? publication-title: IEEE Trans. Biom. Behav. Identity Sci. doi: 10.1109/TBIOM.2020.3027269 – ident: CR8 – ident: CR58 – volume: 31 start-page: 1352 year: 2021 end-page: 1379 ident: CR7 article-title: Sequential quadratic optimization for nonlinear equality constrained stochastic optimization publication-title: SIAM J. Optim. doi: 10.1137/20M1354556 – ident: CR25 – volume: 11 start-page: 1193 year: 2017 end-page: 1216 ident: CR57 article-title: The problem of infra-marginality in outcome tests for discrimination publication-title: Ann. Appl. Stat. doi: 10.1214/17-AOAS1058 – ident: CR21 – ident: CR46 – ident: CR71 – ident: CR19 – volume: 20 start-page: 1 year: 2019 end-page: 42 ident: CR70 article-title: Fairness constraints: a flexible approach for fair classification publication-title: J. Mach. Learn. Res. – ident: CR75 – ident: CR15 – volume: 35 start-page: 58 year: 2017 end-page: 69 ident: CR73 article-title: Computing group cardinality constraint solutions for logistic regression problems publication-title: Med. Image Anal. doi: 10.1016/j.media.2016.05.011 – ident: CR50 – volume: 17 start-page: 251 year: 1979 end-page: 269 ident: CR28 article-title: Exact penalty functions in nonlinear programming publication-title: Math Program. doi: 10.1007/BF01588250 – ident: CR32 – ident: CR60 – ident: CR5 – volume: 6 year: 2021 ident: CR2 article-title: Autonomous driving architectures: Insights of machine learning and deep learning algorithms publication-title: Mach. Learn. Appl. – volume: 8 start-page: 141 year: 2021 end-page: 163 ident: CR52 article-title: Algorithmic fairness: choices, assumptions, and definitions publication-title: Annu. Rev. Stat. Appl. doi: 10.1146/annurev-statistics-042720-125902 – ident: CR64 – ident: CR26 – ident: CR18 – ident: CR43 – ident: CR66 – volume: 19 start-page: 1694 year: 2009 end-page: 1718 ident: CR24 article-title: An adaptive scalarization method in multiobjective optimization publication-title: SIAM J. Optim. doi: 10.1137/060672029 – ident: CR47 – ident: CR14 – ident: CR37 – ident: CR53 – volume: 21 start-page: 277 year: 2010 end-page: 292 ident: CR16 article-title: Three naive Bayes approaches for discrimination-free classification publication-title: Data Min. Knowl. Discov. doi: 10.1007/s10618-010-0190-x – ident: CR30 – ident: CR33 – volume: 100 start-page: 27 issue: 1 year: 2004 end-page: 48 ident: CR12 article-title: An algorithm for nonlinear optimization using linear programming and equality constrained subproblems publication-title: Math. Program. Ser. B – volume: 169 start-page: 932 year: 2006 end-page: 942 ident: CR42 article-title: An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2004.08.029 – ident: CR6 – volume: 63 start-page: 1197 year: 2021 end-page: 1220 ident: CR36 article-title: Expert-driven trace clustering with instance-level constraints publication-title: Knowl. Inf. Syst. doi: 10.1007/s10115-021-01548-6 – ident: CR40 – ident: CR63 – volume: 29 start-page: 4349 year: 2016 end-page: 4357 ident: CR10 article-title: Man is to computer programmer as woman is to homemaker? debiasing word embeddings publication-title: NeurIPS – volume: 42 start-page: 1713 year: 2019 end-page: 1728 ident: CR1 article-title: Logistic regression confined by cardinality-constrained sample and feature selection publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2019.2901688 – volume: 122 start-page: 247 year: 2010 end-page: 272 ident: CR49 article-title: An integer programming approach for linear programs with probabilistic constraints publication-title: Math. Program. doi: 10.1007/s10107-008-0247-4 – ident: CR23 – ident: CR69 – volume: 54 start-page: 88 year: 2019 end-page: 99 ident: CR31 article-title: Constrained-CNN losses for weakly supervised segmentation publication-title: Med. Image Anal. doi: 10.1016/j.media.2019.02.009 – ident: CR44 – volume: 29 start-page: 341 issue: 5–6 year: 2022 end-page: 363 ident: CR27 article-title: Exact algorithms for multiobjective linear optimization problems with integer variables: a state of the art survey publication-title: J. Multi-Criteria Dec Anal doi: 10.1002/mcda.1780 – volume: 73 start-page: 2859 year: 2010 end-page: 2872 ident: CR67 article-title: A novel hypothesis-margin based approach for feature selection with side pairwise constraints publication-title: Neurocomputing doi: 10.1016/j.neucom.2010.08.006 – ident: CR65 – ident: CR3 – ident: CR38 – volume: 60 start-page: 223 issue: 2 year: 2018 end-page: 311 ident: CR11 article-title: Optimization methods for large-scale machine learning publication-title: SIAM Rev. doi: 10.1137/16M1080173 – ident: CR34 – ident: CR55 – ident: CR41 – ident: CR62 – ident: CR20 – ident: 2024_CR61 doi: 10.1145/3194770.3194776 – volume: 20 start-page: 1 year: 2019 ident: 2024_CR70 publication-title: J. Mach. Learn. Res. – volume: 194 start-page: 39 year: 2009 ident: 2024_CR9 publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2007.12.014 – ident: 2024_CR41 – volume: 8 start-page: 141 year: 2021 ident: 2024_CR52 publication-title: Annu. Rev. Stat. Appl. doi: 10.1146/annurev-statistics-042720-125902 – volume: 29 start-page: 341 issue: 5–6 year: 2022 ident: 2024_CR27 publication-title: J. Multi-Criteria Dec Anal doi: 10.1002/mcda.1780 – ident: 2024_CR22 – volume: 122 start-page: 247 year: 2010 ident: 2024_CR49 publication-title: Math. Program. doi: 10.1007/s10107-008-0247-4 – ident: 2024_CR26 – volume: 17 start-page: 251 year: 1979 ident: 2024_CR28 publication-title: Math Program. doi: 10.1007/BF01588250 – volume: 35 start-page: 58 year: 2017 ident: 2024_CR73 publication-title: Med. Image Anal. doi: 10.1016/j.media.2016.05.011 – ident: 2024_CR74 doi: 10.1007/978-3-319-46493-0_40 – ident: 2024_CR32 – ident: 2024_CR15 doi: 10.1109/ICDMW.2009.83 – volume: 29 start-page: 4349 year: 2016 ident: 2024_CR10 publication-title: NeurIPS – volume: 16 start-page: 471 issue: 2 year: 2006 ident: 2024_CR13 publication-title: SIAM J. Optim. doi: 10.1137/S1052623403426532 – ident: 2024_CR55 doi: 10.1007/BFb0067703 – ident: 2024_CR75 doi: 10.1109/ICCV.2019.01077 – ident: 2024_CR19 – ident: 2024_CR51 – ident: 2024_CR3 – volume: 42 start-page: 1713 year: 2019 ident: 2024_CR1 publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2019.2901688 – ident: 2024_CR40 – ident: 2024_CR66 doi: 10.1109/CVPR.2019.01146 – ident: 2024_CR45 doi: 10.1007/s10479-021-04033-z – ident: 2024_CR23 – ident: 2024_CR44 – ident: 2024_CR69 – ident: 2024_CR65 – ident: 2024_CR21 doi: 10.1109/ICASSP.2013.6639344 – ident: 2024_CR54 – ident: 2024_CR64 doi: 10.1109/CVPR42600.2020.00225 – ident: 2024_CR4 – volume: 3 start-page: 101 year: 2020 ident: 2024_CR17 publication-title: IEEE Trans. Biom. Behav. Identity Sci. doi: 10.1109/TBIOM.2020.3027269 – volume: 73 start-page: 2859 year: 2010 ident: 2024_CR67 publication-title: Neurocomputing doi: 10.1016/j.neucom.2010.08.006 – volume: 54 start-page: 88 year: 2019 ident: 2024_CR31 publication-title: Med. Image Anal. doi: 10.1016/j.media.2019.02.009 – ident: 2024_CR33 – volume: 60 start-page: 223 issue: 2 year: 2018 ident: 2024_CR11 publication-title: SIAM Rev. doi: 10.1137/16M1080173 – ident: 2024_CR37 – ident: 2024_CR58 – ident: 2024_CR71 – ident: 2024_CR30 doi: 10.1007/978-3-642-33486-3_3 – volume: 19 start-page: 674 issue: 2 year: 2008 ident: 2024_CR48 publication-title: SIAM J. Optim. doi: 10.1137/070702928 – ident: 2024_CR43 – ident: 2024_CR14 – ident: 2024_CR20 – ident: 2024_CR47 – ident: 2024_CR62 – ident: 2024_CR53 – volume: 100 start-page: 27 issue: 1 year: 2004 ident: 2024_CR12 publication-title: Math. Program. Ser. B – ident: 2024_CR60 doi: 10.1007/978-3-540-74958-5_34 – ident: 2024_CR8 doi: 10.1177/0049124118782533 – ident: 2024_CR34 – ident: 2024_CR38 – volume: 11 start-page: 1193 year: 2017 ident: 2024_CR57 publication-title: Ann. Appl. Stat. doi: 10.1214/17-AOAS1058 – volume: 21 start-page: 277 year: 2010 ident: 2024_CR16 publication-title: Data Min. Knowl. Discov. doi: 10.1007/s10618-010-0190-x – ident: 2024_CR63 – volume: 41 start-page: 1440 year: 2008 ident: 2024_CR72 publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2007.10.009 – ident: 2024_CR46 – volume: 271 start-page: 808 year: 2018 ident: 2024_CR56 publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2018.05.064 – volume: 31 start-page: 1352 year: 2021 ident: 2024_CR7 publication-title: SIAM J. Optim. doi: 10.1137/20M1354556 – volume: 19 start-page: 1694 year: 2009 ident: 2024_CR24 publication-title: SIAM J. Optim. doi: 10.1137/060672029 – ident: 2024_CR29 – volume: 63 start-page: 1197 year: 2021 ident: 2024_CR36 publication-title: Knowl. Inf. Syst. doi: 10.1007/s10115-021-01548-6 – ident: 2024_CR6 – ident: 2024_CR18 doi: 10.1109/ICASSP40776.2020.9054128 – volume: 6 year: 2021 ident: 2024_CR2 publication-title: Mach. Learn. Appl. – ident: 2024_CR50 doi: 10.1109/CVPRW50498.2020.00369 – ident: 2024_CR35 – volume: 23 start-page: 567 year: 1976 ident: 2024_CR59 publication-title: Nav. Res. Logist. Q. doi: 10.1002/nav.3800230402 – ident: 2024_CR68 doi: 10.1145/3038912.3052660 – ident: 2024_CR25 doi: 10.1007/978-3-030-06167-8_14 – volume: 169 start-page: 932 year: 2006 ident: 2024_CR42 publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2004.08.029 – ident: 2024_CR39 – ident: 2024_CR5 doi: 10.2139/ssrn.2477899 |
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| Snippet | A strategy for fair supervised learning is proposed. It involves formulating an optimization problem to minimize loss subject to a prescribed bound on a... |
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| StartPage | 1975 |
| SubjectTerms | Computational Intelligence Mathematics Mathematics and Statistics Numerical and Computational Physics Operations Research/Decision Theory Optimization Original Paper Simulation |
| Title | Fair machine learning through constrained stochastic optimization and an ϵ-constraint method |
| URI | https://link.springer.com/article/10.1007/s11590-023-02024-6 |
| Volume | 18 |
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