Amanda Coston

According to our database, Amanda Coston authored at least 18 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder Early-stage Deliberations Around Public Sector AI Proposals.

Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein

CoRR, 2024

2023

Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design.

Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein

CoRR, 2023

Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making.

Luke Guerdan, Amanda Coston, Zhiwei Steven Wu, Kenneth Holstein

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Counterfactual Prediction Under Outcome Measurement Error.

Luke Guerdan, Amanda Coston, Kenneth Holstein, Zhiwei Steven Wu

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Examining risks of racial biases in NLP tools for child protective services.

Anjalie Field, Amanda Coston, Nupoor Gandhi, Alexandra Chouldechova, Emily Putnam-Hornstein, David Steier, Yulia Tsvetkov

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Counterfactual Risk Assessments under Unmeasured Confounding.

Ashesh Rambachan, Amanda Coston, Edward H. Kennedy

CoRR, 2022

A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms.

Amanda Coston, Anna Kawakami, Haiyi Zhu, Ken Holstein, Hoda Heidari

CoRR, 2022

2021

Characterizing Fairness Over the Set of Good Models Under Selective Labels.

Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova

Proceedings of the 38th International Conference on Machine Learning, 2021

Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy.

Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020

Proceedings of NeurIPS 2019 Workshop on Machine Learning for the Developing World: Challenges and Risks of ML4D.

Maria De-Arteaga, Tejumade Afonja, Amanda Coston

CoRR, 2020

Counterfactual Predictions under Runtime Confounding.

Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Conditional Learning of Fair Representations.

Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon

Proceedings of the 8th International Conference on Learning Representations, 2020

Counterfactual risk assessments, evaluation, and fairness.

Amanda Coston, Alan Mishler, Edward H. Kennedy, Alexandra Chouldechova

Proceedings of the FAT* '20: Conference on Fairness, 2020

Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate.

Linhong Li, Ren Zuo, Amanda Coston, Jeremy C. Weiss, George H. Chen

Proceedings of the Artificial Intelligence in Medicine, 2020

2019

Counterfactual Risk Assessments, Evaluation, and Fairness.

Amanda Coston, Alexandra Chouldechova, Edward H. Kennedy

CoRR, 2019

Fair Transfer Learning with Missing Protected Attributes.

Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Risk Assessments and Fairness Under Missingness and Confounding.

Amanda Coston

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

Proceedings of NeurIPS 2018 Workshop on Machine Learning for the Developing World: Achieving Sustainable Impact.

Maria De-Arteaga, Amanda Coston, William Herlands

CoRR, 2018