Natalie Dullerud

According to our database, Natalie Dullerud authored at least 14 papers between 2020 and 2024.

Collaborative distances:

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

2024

MoSH: Modeling Multi-Objective Tradeoffs with Soft and Hard Bounds.

Edward Chen, Natalie Dullerud, Thomas Niedermayr, Elizabeth Kidd, Ransalu Senanayake, Pang Wei Koh, Sanmi Koyejo, Carlos Guestrin

CoRR, 2024

2023

Private Multi-Winner Voting for Machine Learning.

Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith M. Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang

Proc. Priv. Enhancing Technol., January, 2023

Confidential-PROFITT: Confidential PROof of FaIr Training of Trees.

Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Nicholas Franzese, Natalie Dullerud, Sébastien Gambs, Nicolas Papernot, Xiao Wang, Adrian Weller

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Proof-of-Learning is Currently More Broken Than You Think.

Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot

Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

2022

On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning.

Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot

CoRR, 2022

Washing The Unwashable : On The (Im)possibility of Fairwashing Detection.

Ali Shahin Shamsabadi, Mohammad Yaghini, Natalie Dullerud, Sierra Calanda Wyllie, Ulrich Aïvodji, Aisha Alaagib, Sébastien Gambs, Nicolas Papernot

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

Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning.

Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi

Proceedings of the Tenth International Conference on Learning Representations, 2022

Improving the Fairness of Chest X-ray Classifiers.

Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

Reading Race: AI Recognises Patient's Racial Identity In Medical Images.

Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns, Leo Anthony Celi, Li-Ching Chen, Ramon Correa, Natalie Dullerud, Marzyeh Ghassemi, Shih-Cheng Huang, Po-Chih Kuo, Matthew P. Lungren, Lyle J. Palmer, Brandon J. Price, Saptarshi Purkayastha, Ayis Pyrros, Luke Oakden-Rayner, Chima Okechukwu, Laleh Seyyed-Kalantari, Hari Trivedi, Ryan Wang, Zachary Zaiman, Haoran Zhang, Judy W. Gichoya

CoRR, 2021

Proof-of-Learning: Definitions and Practice.

Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot

Proceedings of the 42nd IEEE Symposium on Security and Privacy, 2021

CaPC Learning: Confidential and Private Collaborative Learning.

Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang

Proceedings of the 9th International Conference on Learning Representations, 2021

Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness.

Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

An empirical framework for domain generalization in clinical settings.

Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020

Cellular Immunotherapy Treatment Scheduling to Address Antigen Escape.

Natalie Dullerud, Vanessa D. Jonsson

Proceedings of the 59th IEEE Conference on Decision and Control, 2020