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ORCIDVinith M. Suriyakumar
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- affiliation: MIT, Cambridge, MA, USA
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2020 – today
- 2024
[c9]Shomik Jain
, Vinith M. Suriyakumar, Kathleen Creel, Ashia Wilson:
Algorithmic Pluralism: A Structural Approach To Equal Opportunity. FAccT 2024: 197-206- [c8]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, Hugh Brendan McMahan, Vinith Menon Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. ICLR 2024 - [c7]Tanner Andrulis, Gohar Irfan Chaudhry, Vinith M. Suriyakumar, Joel S. Emer, Vivienne Sze:
Architecture-Level Modeling of Photonic Deep Neural Network Accelerators. ISPASS 2024: 307-309 - [i11]Tanner Andrulis, Gohar Irfan Chaudhry, Vinith M. Suriyakumar, Joel S. Emer, Vivienne Sze:
Architecture-Level Modeling of Photonic Deep Neural Network Accelerators. CoRR abs/2405.07266 (2024) - [i10]Vinith M. Suriyakumar, Rohan Alur, Ayush Sekhari, Manish Raghavan, Ashia C. Wilson:
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models. CoRR abs/2410.08074 (2024) - 2023
- [j1]Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith M. Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang:
Private Multi-Winner Voting for Machine Learning. Proc. Priv. Enhancing Technol. 2023(1): 527-555 (2023) - [c6]Vinith Menon Suriyakumar, Marzyeh Ghassemi, Berk Ustun:
When Personalization Harms Performance: Reconsidering the Use of Group Attributes in Prediction. ICML 2023: 33209-33228 - [i9]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith M. Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. CoRR abs/2302.03098 (2023) - [i8]Shomik Jain, Vinith M. Suriyakumar, Ashia Wilson:
Algorithmic Pluralism: A Structural Approach Towards Equal Opportunity. CoRR abs/2305.08157 (2023) - 2022
- [c5]Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta:
Public Data-Assisted Mirror Descent for Private Model Training. ICML 2022: 517-535 - [c4]Vinith M. Suriyakumar, Ashia C. Wilson:
Algorithms that Approximate Data Removal: New Results and Limitations. NeurIPS 2022 - [i7]Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun:
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction. CoRR abs/2206.02058 (2022) - [i6]Vinith M. Suriyakumar, Ashia C. Wilson:
Algorithms that Approximate Data Removal: New Results and Limitations. CoRR abs/2209.12269 (2022) - [i5]Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith Menon Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang:
Private Multi-Winner Voting for Machine Learning. CoRR abs/2211.15410 (2022) - 2021
- [c3]Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi:
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness. FAccT 2021: 149-160 - [c2]Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi:
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. FAccT 2021: 723-734 - [i4]Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, James Tu, Nipaporn Tewattanarat, Sayali Joshi, Andrea Doria, Anna Goldenberg:
3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI. CoRR abs/2103.13497 (2021) - [i3]Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta:
Public Data-Assisted Mirror Descent for Private Model Training. CoRR abs/2112.00193 (2021) - 2020
- [i2]Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, Nipaporn Tewattanarat, Andrea Doria, Anna Goldenberg:
Using Generative Models for Pediatric wbMRI. CoRR abs/2006.00727 (2020) - [i1]Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi:
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings. CoRR abs/2010.06667 (2020)
2010 – 2019
- 2017
- [c1]Vinith M. Suriyakumar, Renee Xu, Csaba Pinter, Gabor Fichtinger:
Open-source software for collision detection in external beam radiation therapy. Image-Guided Procedures 2017: 101351G
Coauthor Index
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