Vinith M. Suriyakumar

22 papers A* 2B 1Journal 15Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Computational challenges arising in algorithmic fairness and health equity with generative AI.
Nat. Comput. Sci.
Vinith M. Suriyakumar, Anna Zink, Maia Hightower, Marzyeh Ghassemi, Brett K. Beaulieu-Jones
2025 J jnl
Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models.
CoRR
Chantal Shaib, Vinith M. Suriyakumar, Levent Sagun, Byron C. Wallace, Marzyeh Ghassemi
2025 J jnl
UCD: Unlearning in LLMs via Contrastive Decoding.
CoRR
Vinith M. Suriyakumar, Ayush Sekhari, Ashia Wilson
2025 J jnl
When Style Breaks Safety: Defending Language Models Against Superficial Style Alignment.
CoRR
Yuxin Xiao, Sana Tonekaboni, Walter Gerych, Vinith M. Suriyakumar, Marzyeh Ghassemi
2024 — conf
Algorithmic Pluralism: A Structural Approach To Equal Opportunity.
FAccT
Shomik Jain, Vinith M. Suriyakumar, Kathleen Creel, Ashia Wilson
2024 B conf
Architecture-Level Modeling of Photonic Deep Neural Network Accelerators.
ISPASS
Tanner Andrulis, Gohar Irfan Chaudhry, Vinith M. Suriyakumar, Joel S. Emer, Vivienne Sze
2024 J jnl
Architecture-Level Modeling of Photonic Deep Neural Network Accelerators.
CoRR
Tanner Andrulis, Gohar Irfan Chaudhry, Vinith M. Suriyakumar, Joel S. Emer, Vivienne Sze
2024 J jnl
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models.
CoRR
Vinith M. Suriyakumar, Rohan Alur, Ayush Sekhari, Manish Raghavan, Ashia C. Wilson
2023 J jnl
Algorithmic Pluralism: A Structural Approach Towards Equal Opportunity.
CoRR
Shomik Jain, Vinith M. Suriyakumar, Ashia Wilson
2023 J jnl
One-shot Empirical Privacy Estimation for Federated Learning.
CoRR
Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith M. Suriyakumar
2023 J jnl
Private Multi-Winner Voting for Machine Learning.
Proc. Priv. Enhancing Technol.
Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith M. Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
2022 A* conf
Algorithms that Approximate Data Removal: New Results and Limitations.
NeurIPS
Vinith M. Suriyakumar, Ashia C. Wilson
2022 J jnl
Algorithms that Approximate Data Removal: New Results and Limitations.
CoRR
Vinith M. Suriyakumar, Ashia C. Wilson
2022 A* conf
Public Data-Assisted Mirror Descent for Private Model Training.
ICML
Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2022 J jnl
When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction.
CoRR
Vinith M. Suriyakumar, Marzyeh Ghassemi, Berk Ustun
2021 J jnl
3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI.
CoRR
Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, James Tu, Nipaporn Tewattanarat, Sayali Joshi, Andrea Doria, Anna Goldenberg
2021 — conf
Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness.
FAccT
Victoria Cheng, Vinith M. Suriyakumar, Natalie Dullerud, Shalmali Joshi, Marzyeh Ghassemi
2021 — conf
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings.
FAccT
Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
2021 J jnl
Public Data-Assisted Mirror Descent for Private Model Training.
CoRR
Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2020 J jnl
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings.
CoRR
Vinith M. Suriyakumar, Nicolas Papernot, Anna Goldenberg, Marzyeh Ghassemi
2020 J jnl
Using Generative Models for Pediatric wbMRI.
CoRR
Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu, Nipaporn Tewattanarat, Andrea Doria, Anna Goldenberg
2017 — conf
Open-source software for collision detection in external beam radiation therapy.
Image-Guided Procedures
Vinith M. Suriyakumar, Renee Xu, Csaba Pinter, Gabor Fichtinger