Joshua R. Loftus

According to our database, Joshua R. Loftus authored at least 16 papers between 2017 and 2024.

Collaborative distances:

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

2024

Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy.

Lucas Rosenblatt, Bernease Herman, Anastasia Holovenko, Wonkwon Lee, Joshua R. Loftus, Elizabeth McKinnie, Taras Rumezhak, Andrii Stadnik, Bill Howe, Julia Stoyanovich

SIGMOD Rec., March, 2024

A New Paradigm for Counterfactual Reasoning in Fairness and Recourse.

Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Position: The Causal Revolution Needs Scientific Pragmatism.

Joshua R. Loftus

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Causal Dependence Plots for Interpretable Machine Learning.

Joshua R. Loftus, Lucius E. J. Bynum, Sakina Hansen

CoRR, 2023

It's About Time: Counterfactual Fairness and Temporal Depth.

Joshua R. Loftus

Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Model-Agnostic Auditing: A Lost Cause?

Sakina Hansen, Joshua R. Loftus

Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Counterfactuals for the Future.

Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

Impact Remediation: Optimal Interventions to Reduce Inequality.

Lucius E. J. Bynum, Joshua R. Loftus, Julia Stoyanovich

CoRR, 2021

Causal Intersectionality and Fair Ranking.

Ke Yang, Joshua R. Loftus, Julia Stoyanovich

Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

Disaggregated Interventions to Reduce Inequality.

Lucius Bynum, Joshua R. Loftus, Julia Stoyanovich

Proceedings of the EAAMO 2021: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual Event, USA, October 5, 2021

2020

Causal intersectionality for fair ranking.

Ke Yang, Joshua R. Loftus, Julia Stoyanovich

CoRR, 2020

2019

Making Decisions that Reduce Discriminatory Impacts.

Matt J. Kusner, Chris Russell, Joshua R. Loftus, Ricardo Silva

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Causal Interventions for Fairness.

Matt J. Kusner, Chris Russell, Joshua R. Loftus, Ricardo Silva

CoRR, 2018

Causal Reasoning for Algorithmic Fairness.

Joshua R. Loftus, Chris Russell, Matt J. Kusner, Ricardo Silva

CoRR, 2018

2017

When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness.

Chris Russell, Matt J. Kusner, Joshua R. Loftus, Ricardo Silva

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Counterfactual Fairness.

Matt J. Kusner, Joshua R. Loftus, Chris Russell, Ricardo Silva

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017