Amanda Coston

35 papers A* 5B 1C 2Journal 21Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
Falsifying Predictive Algorithm.
CoRR
Amanda Coston
2025 J jnl
Bridging Prediction and Intervention Problems in Social Systems.
CoRR
Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Hammaad Adam, Amanda Coston, Benjamin Laufer, Ezinne Nwankwo, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson
2024 J jnl
Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relate.
Artif. Intell. Medicine
George H. Chen, Linhong Li, Ren Zuo, Amanda Coston, Jeremy C. Weiss
2024 A* conf
Predictive Performance Comparison of Decision Policies Under Confounding.
ICML
Luke Guerdan, Amanda Coston, Ken Holstein, Steven Wu
2024 J jnl
Predictive Performance Comparison of Decision Policies Under Confounding.
CoRR
Luke Guerdan, Amanda Coston, Kenneth Holstein, Zhiwei Steven Wu
2024 J jnl
Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use.
CoRR
Anna Kawakami, Amanda Coston, Hoda Heidari, Kenneth Holstein, Haiyi Zhu
2024 J jnl
Studying Up Public Sector AI: How Networks of Power Relations Shape Agency Decisions Around AI Design and Use.
Proc. ACM Hum. Comput. Interact.
Anna Kawakami, Amanda Coston, Hoda Heidari, Kenneth Holstein, Haiyi Zhu
2024 J jnl
The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder Early-stage Deliberations Around Public Sector AI Proposals.
CoRR
Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein
2024 A* conf
The Situate AI Guidebook: Co-Designing a Toolkit to Support Multi-Stakeholder, Early-stage Deliberations Around Public Sector AI Proposals.
CHI
Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein
2023 — conf
A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms.
SaTML
Amanda Coston, Anna Kawakami, Haiyi Zhu, Ken Holstein, Hoda Heidari
2023 — conf
Counterfactual Prediction Under Outcome Measurement Error.
FAccT
Luke Guerdan, Amanda Coston, Kenneth Holstein, Zhiwei Steven Wu
2023 J jnl
Counterfactual Prediction Under Outcome Measurement Error.
CoRR
Luke Guerdan, Amanda Coston, Kenneth Holstein, Zhiwei Steven Wu
2023 — conf
Examining risks of racial biases in NLP tools for child protective services.
FAccT
Anjalie Field, Amanda Coston, Nupoor Gandhi, Alexandra Chouldechova, Emily Putnam-Hornstein, David Steier, Yulia Tsvetkov
2023 J jnl
Examining risks of racial biases in NLP tools for child protective services.
CoRR
Anjalie Field, Amanda Coston, Nupoor Gandhi, Alexandra Chouldechova, Emily Putnam-Hornstein, David Steier, Yulia Tsvetkov
2023 — conf
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making.
FAccT
Luke Guerdan, Amanda Coston, Zhiwei Steven Wu, Kenneth Holstein
2023 J jnl
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making.
CoRR
Luke Guerdan, Amanda Coston, Zhiwei Steven Wu, Kenneth Holstein
2023 J jnl
Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design.
CoRR
Anna Kawakami, Amanda Coston, Haiyi Zhu, Hoda Heidari, Kenneth Holstein
2022 J jnl
A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms.
CoRR
Amanda Coston, Anna Kawakami, Haiyi Zhu, Ken Holstein, Hoda Heidari
2022 J jnl
Counterfactual Risk Assessments under Unmeasured Confounding.
CoRR
Ashesh Rambachan, Amanda Coston, Edward H. Kennedy
2021 A* conf
Characterizing Fairness Over the Set of Good Models Under Selective Labels.
ICML
Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova
2021 J jnl
Characterizing Fairness Over the Set of Good Models Under Selective Labels.
CoRR
Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova
2021 — conf
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy.
FAccT
Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho
2020 A* conf
Conditional Learning of Fair Representations.
ICLR
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
2020 A* conf
Counterfactual Predictions under Runtime Confounding.
NeurIPS
Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova
2020 J jnl
Counterfactual Predictions under Runtime Confounding.
CoRR
Amanda Coston, Edward H. Kennedy, Alexandra Chouldechova
2020 — conf
Counterfactual risk assessments, evaluation, and fairness.
FAT*
Amanda Coston, Alan Mishler, Edward H. Kennedy, Alexandra Chouldechova
2020 J jnl
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy.
CoRR
Amanda Coston, Neel Guha, Derek Ouyang, Lisa Lu, Alexandra Chouldechova, Daniel E. Ho
2020 B conf
Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate.
AIME
Linhong Li, Ren Zuo, Amanda Coston, Jeremy C. Weiss, George H. Chen
2020 J jnl
Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate.
CoRR
Linhong Li, Ren Zuo, Amanda Coston, Jeremy C. Weiss, George H. Chen
2020 J jnl
Proceedings of NeurIPS 2019 Workshop on Machine Learning for the Developing World: Challenges and Risks of ML4D.
CoRR
Maria De-Arteaga, Tejumade Afonja, Amanda Coston
2019 J jnl
Conditional Learning of Fair Representations.
CoRR
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
2019 J jnl
Counterfactual Risk Assessments, Evaluation, and Fairness.
CoRR
Amanda Coston, Alexandra Chouldechova, Edward H. Kennedy
2019 C conf
Fair Transfer Learning with Missing Protected Attributes.
AIES
Amanda Coston, Karthikeyan Natesan Ramamurthy, Dennis Wei, Kush R. Varshney, Skyler Speakman, Zairah Mustahsan, Supriyo Chakraborty
2019 C conf
Risk Assessments and Fairness Under Missingness and Confounding.
AIES
Amanda Coston
2018 J jnl
Proceedings of NeurIPS 2018 Workshop on Machine Learning for the Developing World: Achieving Sustainable Impact.
CoRR
Maria De-Arteaga, Amanda Coston, William Herlands