Christopher Jung

According to our database, Christopher Jung authored at least 21 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Orthogonal Causal Calibration.

Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu

CoRR, 2024

Taking a Moment for Distributional Robustness.

Jabari Hastings, Christopher Jung, Charlotte Peale, Vasilis Syrgkanis

CoRR, 2024

Oracle Efficient Online Multicalibration and Omniprediction.

Sumegha Garg, Christopher Jung, Omer Reingold, Aaron Roth

Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

2023

Batch Multivalid Conformal Prediction.

Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Distributionally Robust Data Join.

Pranjal Awasthi, Christopher Jung, Jamie Morgenstern

Proceedings of the 4th Symposium on Foundations of Responsible Computing, 2023

Multicalibrated Regression for Downstream Fairness.

Ira Globus-Harris, Varun Gupta, Christopher Jung, Michael Kearns, Jamie Morgenstern, Aaron Roth

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Practical Adversarial Multivalid Conformal Prediction.

Osbert Bastani, Varun Gupta, Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Multivalid Learning: Means, Moments, and Prediction Intervals.

Varun Gupta, Christopher Jung, Georgy Noarov, Mallesh M. Pai, Aaron Roth

Proceedings of the 13th Innovations in Theoretical Computer Science Conference, 2022

2021

A new analysis of differential privacy's generalization guarantees (invited paper).

Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Adaptive Machine Unlearning.

Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Algorithmic Framework for Fairness Elicitation.

Christopher Jung, Michael Kearns, Seth Neel, Aaron Roth, Logan Stapleton, Zhiwei Steven Wu

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

Moment Multicalibration for Uncertainty Estimation.

Christopher Jung, Changhwa Lee, Mallesh M. Pai, Aaron Roth, Rakesh Vohra

Proceedings of the Conference on Learning Theory, 2021

2020

Quantifying the Burden of Exploration and the Unfairness of Free Riding.

Christopher Jung, Sampath Kannan, Neil Lutz

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Fair Prediction with Endogenous Behavior.

Christopher Jung, Sampath Kannan, Changhwa Lee, Mallesh M. Pai, Aaron Roth, Rakesh Vohra

Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Metric-Free Individual Fairness in Online Learning.

Yahav Bechavod, Christopher Jung, Zhiwei Steven Wu

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

A New Analysis of Differential Privacy's Generalization Guarantees.

Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld

Proceedings of the 11th Innovations in Theoretical Computer Science Conference, 2020

Service in Your Neighborhood: Fairness in Center Location.

Christopher Jung, Sampath Kannan, Neil Lutz

Proceedings of the 1st Symposium on Foundations of Responsible Computing, 2020

2019

A Center in Your Neighborhood: Fairness in Facility Location.

Christopher Jung, Sampath Kannan, Neil Lutz

CoRR, 2019

Eliciting and Enforcing Subjective Individual Fairness.

Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Logan Stapleton, Zhiwei Steven Wu

CoRR, 2019

Fair Algorithms for Learning in Allocation Problems.

Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Zachary Schutzman

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018

Online Learning with an Unknown Fairness Metric.

Stephen Gillen, Christopher Jung, Michael J. Kearns, Aaron Roth

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018