| Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings VM Suriyakumar, N Papernot, A Goldenberg, M Ghassemi ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2021, 2020 | 75 | 2020 |
| Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness V Cheng, VM Suriyakumar, N Dullerud, S Joshi, M Ghassemi ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2021, 2020 | 64 | 2020 |
| Public Data-Assisted Mirror Descent for Private Model Training E Amid, A Ganesh, R Matthews, S Ramaswamy, S Song, T Steinke, ... https://arxiv.org/abs/2112.00193, 2021 | 62 | 2021 |
| One-shot empirical privacy estimation for federated learning G Andrew, P Kairouz, S Oh, A Oprea, HB McMahan, VM Suriyakumar arXiv preprint arXiv:2302.03098, 2023 | 35 | 2023 |
| Algorithms that Approximate Data Removal: New Results and Limitations VM Suriyakumar, AC Wilson NeurIPS 2022, 2022 | 26 | 2022 |
| When personalization harms: Reconsidering the use of group attributes in prediction VM Suriyakumar, M Ghassemi, B Ustun arXiv preprint arXiv:2206.02058, 2022 | 18 | 2022 |
| Algorithmic pluralism: A structural approach to equal opportunity S Jain, V Suriyakumar, K Creel, A Wilson Proceedings of the 2024 ACM Conference on Fairness, Accountability, and …, 2024 | 16 | 2024 |
| When personalization harms performance: reconsidering the use of group attributes in prediction VM Suriyakumar, M Ghassemi, B Ustun International Conference on Machine Learning, 33209-33228, 2023 | 7 | 2023 |
| Using Generative Models for Pediatric wbMRI A Chang, VM Suriyakumar, A Moturu, N Tewattanarat, A Doria, ... Medical Imaging in Deep Learning, 2020 | 6 | 2020 |
| Open-source software for collision detection in external beam radiation therapy VM Suriyakumar, R Xu, C Pinter, G Fichtinger Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and …, 2017 | 6 | 2017 |
| Challenges of differentially private prediction in healthcare settings VM Suriyakumar, N Papernot, A Goldenberg, M Ghassemi Proceedings of the IJCAI 2021 Workshop on AI for Social Good, 2021 | 4 | 2021 |
| Architecture-level modeling of photonic deep neural network accelerators T Andrulis, GI Chaudhry, VM Suriyakumar, JS Emer, V Sze 2024 IEEE International Symposium on Performance Analysis of Systems and …, 2024 | 2 | 2024 |
| Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models VM Suriyakumar, R Alur, A Sekhari, M Raghavan, AC Wilson | | 2024 |
| Leveraging Public Data in Training Neural Networks with Private Mirror Descent OD Thakkar, E Amid, A Ganesh, R Mathews, S Ramaswamy, S Song, ... US Patent App. 17/937,825, 2023 | | 2023 |
| Private Multi-Winner Voting for Machine Learning A Dziedzic, CA Choquette-Choo, N Dullerud, VM Suriyakumar, ... arXiv preprint arXiv:2211.15410, 2022 | | 2022 |
| 3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI A Chang, V Suriyakumar, A Moturu, J Tu, N Tewattanarat, S Joshi, A Doria, ... arXiv preprint arXiv:2103.13497, 2021 | | 2021 |
| The Revealed Preferences of Pre-authorized Licenses and Their Ethical Implications for Generative Models VM Suriyakumar, P Menell, D Hadfield-Menell, A Wilson | | |
| Limits of Algorithmic Stability for Distributional Generalization N Hulkund, VM Suriyakumar, TW Killian, M Ghassemi | | |