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Alexandra Chouldechova
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2020 – today
- 2024
- [c25]Christine Herlihy
, Kimberly Truong
A structured regression approach for evaluating model performance across intersectional subgroups. FAccT 2024: 313-325 - [c24]Nil-Jana Akpinar
The Impact of Differential Feature Under-reporting on Algorithmic Fairness. FAccT 2024: 1355-1382 - [i30]Nil-Jana Akpinar, Zachary C. Lipton, Alexandra Chouldechova:
The Impact of Differential Feature Under-reporting on Algorithmic Fairness. CoRR abs/2401.08788 (2024) - [i29]Christine Herlihy, Kimberly Truong, Alexandra Chouldechova, Miroslav Dudík:
A structured regression approach for evaluating model performance across intersectional subgroups. CoRR abs/2401.14893 (2024) - [i28]Lingwei Cheng, Cameron Drayton, Alexandra Chouldechova, Rhema Vaithianathan:
Algorithm-Assisted Decision Making and Racial Disparities in Housing: A Study of the Allegheny Housing Assessment Tool. CoRR abs/2407.21209 (2024) - [i27]Anna Kawakami, Daricia Wilkinson, Alexandra Chouldechova:
Do Responsible AI Artifacts Advance Stakeholder Goals? Four Key Barriers Perceived by Legal and Civil Stakeholders. CoRR abs/2408.12047 (2024) - 2023
- [c23]Lingwei Cheng
Overcoming Algorithm Aversion: A Comparison between Process and Outcome Control. CHI 2023: 756:1-756:27 - [c22]Jamelle Watson-Daniels
Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints. FAccT 2023: 297-311 - [c21]Anjalie Field
Examining risks of racial biases in NLP tools for child protective services. FAccT 2023: 1479-1492 - [i26]Lingwei Cheng, Alexandra Chouldechova:
Overcoming Algorithm Aversion: A Comparison between Process and Outcome Control. CoRR abs/2303.12896 (2023) - [i25]Anjalie Field, Amanda Coston, Nupoor Gandhi, Alexandra Chouldechova, Emily Putnam-Hornstein, David Steier, Yulia Tsvetkov:
Examining risks of racial biases in NLP tools for child protective services. CoRR abs/2305.19409 (2023) - [i24]Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova:
Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints. CoRR abs/2306.13738 (2023) - 2022
- [j5]Lingwei Cheng
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening. Proc. ACM Hum. Comput. Interact. 6(CSCW2): 1-33 (2022) - [c20]Alexandra Chouldechova, Siqi Deng, Yongxin Wang, Wei Xia, Pietro Perona:
Unsupervised and Semi-supervised Bias Benchmarking in Face Recognition. ECCV (13) 2022: 289-306 - [c19]Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu
Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders. FAccT 2022: 1162-1177 - [c18]Emily Black
Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models. FAccT 2022: 1479-1503 - [c17]Kate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi:
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness. FAccT 2022: 1639-1656 - [i23]Kate Donahue, Alexandra Chouldechova, Krishnaram Kenthapadi:
Human-Algorithm Collaboration: Achieving Complementarity and Avoiding Unfairness. CoRR abs/2202.08821 (2022) - [i22]Lingwei Cheng, Alexandra Chouldechova:
Heterogeneity in Algorithm-Assisted Decision-Making: A Case Study in Child Abuse Hotline Screening. CoRR abs/2204.05478 (2022) - [i21]Maria De-Arteaga, Alexandra Chouldechova, Artur Dubrawski:
Doubting AI Predictions: Influence-Driven Second Opinion Recommendation. CoRR abs/2205.00072 (2022) - [i20]Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Kenneth Holstein, Zhiwei Steven Wu, Haiyi Zhu:
Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders. CoRR abs/2205.08928 (2022) - [i19]Emily Black, Hadi Elzayn, Alexandra Chouldechova, Jacob Goldin, Daniel E. Ho:
Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models. CoRR abs/2206.09875 (2022) - 2021
- [j4]Rhema Vaithianathan, Diana Benavides Prado
Using a Machine Learning Tool to Support High-Stakes Decisions in Child Protection. AI Mag. 42(1): 53-60 (2021) - [j3]Riccardo Fogliato, Alexandra Chouldechova, Zachary C. Lipton:
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies. Proc. ACM Hum. Comput. Interact. 5(CSCW2): 428:1-428:24 (2021) - [c16]Riccardo Fogliato, Alice Xiang
On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes. AIES 2021: 100-111 - [c15]Hao Fei Cheng
Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems. CHI 2021: 390:1-390:17 - [c14]Amanda Coston
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy. FAccT 2021: 173-184 - [c13]Alan Mishler
Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds. FAccT 2021: 386-400 - [c12]Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova:
The effect of differential victim crime reporting on predictive policing systems. FAccT 2021: 838-849 - [c11]Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova:
Characterizing Fairness Over the Set of Good Models Under Selective Labels. ICML 2021: 2144-2155 - [i18]Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova:
Characterizing Fairness Over the Set of Good Models Under Selective Labels. CoRR abs/2101.00352 (2021) - [i17]Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova:
Leveraging Expert Consistency to Improve Algorithmic Decision Support. CoRR abs/2101.09648 (2021) - [i16]Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova:
The effect of differential victim crime reporting on predictive policing systems. CoRR abs/2102.00128 (2021) - [i15]Hao Fei Cheng, Logan Stapleton, Ruiqi Wang, Paige Bullock, Alexandra Chouldechova, Zhiwei Steven Wu, Haiyi Zhu:
Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems. CoRR abs/2102.01196 (2021) - [i14]Riccardo Fogliato, Alexandra Chouldechova, Zachary C. Lipton:
The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies. CoRR abs/2109.01443 (2021) - 2020
- [j2]Alexandra Chouldechova, Aaron Roth
A snapshot of the frontiers of fairness in machine learning. Commun. ACM 63(5): 82-89 (2020) - [c10]Riccardo Fogliato, Alexandra Chouldechova, Max G'Sell:
Fairness Evaluation in Presence of Biased Noisy Labels. AISTATS 2020: 2325-2336 - [c9]Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova:
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores. CHI 2020: 1-12 - [c8]Amanda Coston
Counterfactual risk assessments, evaluation, and fairness. FAT* 2020: 582-593 - [c7]Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova:
Counterfactual Predictions under Runtime Confounding. NeurIPS 2020 - [i13]Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova:
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores. CoRR abs/2002.08035 (2020) - [i12]Riccardo Fogliato, Max G'Sell, Alexandra Chouldechova:
Fairness Evaluation in Presence of Biased Noisy Labels. CoRR abs/2003.13808 (2020) - [i11]Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova:
Counterfactual Predictions under Runtime Confounding. CoRR abs/2006.16916 (2020) - [i10]Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho:
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy. CoRR abs/2011.07194 (2020)
2010 – 2019
- 2019
- [c6]Anna Brown
Toward Algorithmic Accountability in Public Services: A Qualitative Study of Affected Community Perspectives on Algorithmic Decision-making in Child Welfare Services. CHI 2019: 41 - [c5]Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT 2019: 120-128 - [c4]Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. NAACL-HLT (1) 2019: 4187-4195 - [i9]Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai:
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR abs/1901.09451 (2019) - [i8]Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai:
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR abs/1904.05233 (2019) - [i7]Amanda Coston, Alexandra Chouldechova, Edward H. Kennedy:
Counterfactual Risk Assessments, Evaluation, and Fairness. CoRR abs/1909.00066 (2019) - 2018
- [c3]Alexandra Chouldechova, Diana Benavides Prado
A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. FAT 2018: 134-148 - [c2]Zachary C. Lipton, Julian J. McAuley, Alexandra Chouldechova:
Does mitigating ML's impact disparity require treatment disparity? NeurIPS 2018: 8136-8146 - [i6]Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova:
Learning under selective labels in the presence of expert consistency. CoRR abs/1807.00905 (2018) - [i5]Alexandra Chouldechova, Aaron Roth:
The Frontiers of Fairness in Machine Learning. CoRR abs/1810.08810 (2018) - 2017
- [j1]Alexandra Chouldechova:
Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments. Big Data 5(2): 153-163 (2017) - [i4]Alexandra Chouldechova:
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. CoRR abs/1703.00056 (2017) - [i3]Alexandra Chouldechova, Max G'Sell:
Fairer and more accurate, but for whom? CoRR abs/1707.00046 (2017) - [i2]Zachary C. Lipton, Alexandra Chouldechova, Julian J. McAuley:
Does mitigating ML's disparate impact require disparate treatment? CoRR abs/1711.07076 (2017) - 2016
- [i1]Alexandra Chouldechova:
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. CoRR abs/1610.07524 (2016) - 2013
- [c1]Alexandra Chouldechova, David Mease:
Differences in search engine evaluations between query owners and non-owners. WSDM 2013: 103-112
Coauthor Index
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last updated on 2024-10-07 21:11 CEST by the dblp team
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