Serena Lutong Wang

Orcid: 0000-0001-9664-4609

According to our database1, Serena Lutong Wang authored at least 25 papers between 2018 and 2024.

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Bibliography

2024
Expected Pinball Loss For Quantile Regression And Inverse CDF Estimation.
Trans. Mach. Learn. Res., 2024

Information Elicitation in Agency Games.
CoRR, 2024

Score Design for Multi-Criteria Incentivization.
Proceedings of the 5th Symposium on Foundations of Responsible Computing, 2024

On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information Asymmetry.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Operationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry.
CoRR, 2023

Robust distillation for worst-class performance: on the interplay between teacher and student objectives.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022
Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias.
Trans. Mach. Learn. Res., 2022

'It's Problematic but I'm not Concerned': University Perspectives on Account Sharing.
Proc. ACM Hum. Comput. Interact., 2022

Lost in Translation: Reimagining the Machine Learning Life Cycle in Education.
CoRR, 2022

Robust Distillation for Worst-class Performance.
CoRR, 2022

2021
Quit When You Can: Efficient Evaluation of Ensembles by Optimized Ordering.
ACM J. Emerg. Technol. Comput. Syst., 2021

Multi-Source Causal Inference Using Control Variates.
CoRR, 2021

Regularization Strategies for Quantile Regression.
CoRR, 2021

Variational refinement for importance sampling using the forward Kullback-Leibler divergence.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020
Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty.
CoRR, 2020

Robust Optimization for Fairness with Noisy Protected Groups.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Approximate Heavily-Constrained Learning with Lagrange Multiplier Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deontological Ethics By Monotonicity Shape Constraints.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Pairwise Fairness for Ranking and Regression.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals.
J. Mach. Learn. Res., 2019

Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints.
Proceedings of the 36th International Conference on Machine Learning, 2019

Shape Constraints for Set Functions.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Proxy Fairness.
CoRR, 2018

Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization.
CoRR, 2018

Interpretable Set Functions.
CoRR, 2018


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