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Christopher Jung 0001
Person information
- affiliation: Stanford University, CA, USA
- affiliation (PhD): University of Pennsylvania, Philadelphia, PA, USA
Other persons with the same name
- Christopher Jung 0002 — Karlsruhe Institute of Technology, Germany
- Christopher Jung 0003 — University of Münster, School of Business and Economics, Germany
- Christopher Jung 0004 — University of Freiburg, Chair of Environmental Meteorology, Germany
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2020 – today
- 2024
- [c17]Sumegha Garg, Christopher Jung, Omer Reingold, Aaron Roth:
Oracle Efficient Online Multicalibration and Omniprediction. SODA 2024: 2725-2792 - [i18]Jabari Hastings, Christopher Jung, Charlotte Peale, Vasilis Syrgkanis:
Taking a Moment for Distributional Robustness. CoRR abs/2405.05461 (2024) - [i17]Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis, Bryan Wilder, Zhiwei Steven Wu:
Orthogonal Causal Calibration. CoRR abs/2406.01933 (2024) - 2023
- [c16]Ira Globus-Harris, Varun Gupta, Christopher Jung, Michael Kearns, Jamie Morgenstern, Aaron Roth:
Multicalibrated Regression for Downstream Fairness. AIES 2023: 259-286 - [c15]Pranjal Awasthi, Christopher Jung, Jamie Morgenstern:
Distributionally Robust Data Join. FORC 2023: 10:1-10:15 - [c14]Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth:
Batch Multivalid Conformal Prediction. ICLR 2023 - [i16]Sumegha Garg, Christopher Jung, Omer Reingold, Aaron Roth:
Oracle Efficient Online Multicalibration and Omniprediction. CoRR abs/2307.08999 (2023) - 2022
- [c13]Varun Gupta, Christopher Jung, Georgy Noarov, Mallesh M. Pai, Aaron Roth:
Online Multivalid Learning: Means, Moments, and Prediction Intervals. ITCS 2022: 82:1-82:24 - [c12]Osbert Bastani, Varun Gupta, Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth:
Practical Adversarial Multivalid Conformal Prediction. NeurIPS 2022 - [i15]Pranjal Awasthi, Christopher Jung, Jamie Morgenstern:
Distributionally Robust Data Join. CoRR abs/2202.05797 (2022) - [i14]Osbert Bastani, Varun Gupta, Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth:
Practical Adversarial Multivalid Conformal Prediction. CoRR abs/2206.01067 (2022) - [i13]Ira Globus-Harris, Varun Gupta, Christopher Jung, Michael Kearns, Jamie Morgenstern, Aaron Roth:
Multicalibrated Regression for Downstream Fairness. CoRR abs/2209.07312 (2022) - [i12]Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth:
Batch Multivalid Conformal Prediction. CoRR abs/2209.15145 (2022) - 2021
- [c11]Christopher Jung, Changhwa Lee, Mallesh M. Pai, Aaron Roth, Rakesh Vohra:
Moment Multicalibration for Uncertainty Estimation. COLT 2021: 2634-2678 - [c10]Christopher Jung, Michael Kearns, Seth Neel, Aaron Roth, Logan Stapleton, Zhiwei Steven Wu:
An Algorithmic Framework for Fairness Elicitation. FORC 2021: 2:1-2:19 - [c9]Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites:
Adaptive Machine Unlearning. NeurIPS 2021: 16319-16330 - [c8]Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld:
A new analysis of differential privacy's generalization guarantees (invited paper). STOC 2021: 9 - [i11]Varun Gupta, Christopher Jung, Georgy Noarov, Mallesh M. Pai, Aaron Roth:
Online Multivalid Learning: Means, Moments, and Prediction Intervals. CoRR abs/2101.01739 (2021) - [i10]Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites:
Adaptive Machine Unlearning. CoRR abs/2106.04378 (2021) - 2020
- [c7]Christopher Jung, Sampath Kannan, Neil Lutz:
Service in Your Neighborhood: Fairness in Center Location. FORC 2020: 5:1-5:15 - [c6]Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld:
A New Analysis of Differential Privacy's Generalization Guarantees. ITCS 2020: 31:1-31:17 - [c5]Yahav Bechavod, Christopher Jung, Zhiwei Steven Wu:
Metric-Free Individual Fairness in Online Learning. NeurIPS 2020 - [c4]Christopher Jung, Sampath Kannan, Changhwa Lee, Mallesh M. Pai, Aaron Roth, Rakesh Vohra:
Fair Prediction with Endogenous Behavior. EC 2020: 677-678 - [c3]Christopher Jung, Sampath Kannan, Neil Lutz:
Quantifying the Burden of Exploration and the Unfairness of Free Riding. SODA 2020: 1892-1904 - [i9]Yahav Bechavod, Christopher Jung, Zhiwei Steven Wu:
Metric-Free Individual Fairness in Online Learning. CoRR abs/2002.05474 (2020) - [i8]Christopher Jung, Sampath Kannan, Changhwa Lee, Mallesh M. Pai, Aaron Roth, Rakesh Vohra:
Fair Prediction with Endogenous Behavior. CoRR abs/2002.07147 (2020) - [i7]Christopher Jung, Changhwa Lee, Mallesh M. Pai, Aaron Roth, Rakesh Vohra:
Moment Multicalibration for Uncertainty Estimation. CoRR abs/2008.08037 (2020)
2010 – 2019
- 2019
- [c2]Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Zachary Schutzman:
Fair Algorithms for Learning in Allocation Problems. FAT 2019: 170-179 - [i6]Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Logan Stapleton, Zhiwei Steven Wu:
Eliciting and Enforcing Subjective Individual Fairness. CoRR abs/1905.10660 (2019) - [i5]Christopher Jung, Sampath Kannan, Neil Lutz:
A Center in Your Neighborhood: Fairness in Facility Location. CoRR abs/1908.09041 (2019) - [i4]Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld:
A New Analysis of Differential Privacy's Generalization Guarantees. CoRR abs/1909.03577 (2019) - 2018
- [c1]Stephen Gillen, Christopher Jung, Michael J. Kearns, Aaron Roth:
Online Learning with an Unknown Fairness Metric. NeurIPS 2018: 2605-2614 - [i3]Stephen Gillen, Christopher Jung, Michael J. Kearns, Aaron Roth:
Online Learning with an Unknown Fairness Metric. CoRR abs/1802.06936 (2018) - [i2]Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Roth, Zachary Schutzman:
Fair Algorithms for Learning in Allocation Problems. CoRR abs/1808.10549 (2018) - [i1]Christopher Jung, Sampath Kannan, Neil Lutz:
Quantifying the Burden of Exploration and the Unfairness of Free Riding. CoRR abs/1810.08743 (2018)
Coauthor Index
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