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ORCIDVaikkunth Mugunthan
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2020 – today
- 2024
[i11]Blazej Manczak, Eliott Zemour, Eric Lin, Vaikkunth Mugunthan:
PrimeGuard: Safe and Helpful LLMs through Tuning-Free Routing. CoRR abs/2407.16318 (2024)- 2023
- [j1]Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Irina Rish, Eugene Belilovsky:
Gradient Masked Averaging for Federated Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c9]Taehyeon Kim, Eric Lin, Junu Lee, Christian Lau, Vaikkunth Mugunthan:
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Approach for Object Detection. NeurIPS 2023 - [i10]Albert Yu Sun, Eliott Zemour, Arushi Saxena, Udith Vaidyanathan, Eric Lin, Christian Lau, Vaikkunth Mugunthan:
Does fine-tuning GPT-3 with the OpenAI API leak personally-identifiable information? CoRR abs/2307.16382 (2023) - [i9]Taehyeon Kim, Eric Lin, Junu Lee, Christian Lau, Vaikkunth Mugunthan:
Navigating Data Heterogeneity in Federated Learning A Semi-Supervised Approach for Object Detection. CoRR abs/2310.17097 (2023) - 2022
- [b1]Vaikkunth Mugunthan:
A Practical Approach to Federated Learning. MIT, USA, 2022 - [c8]Kevin Fang, Vaikkunth Mugunthan, Vayd Ramkumar, Lalana Kagal:
Overcoming Challenges of Synthetic Data Generation. IEEE Big Data 2022: 262-270 - [c7]Vaikkunth Mugunthan, Eric Lin, Vignesh Gokul, Christian Lau, Lalana Kagal, Steven D. Pieper:
FedLTN: Federated Learning for Sparse and Personalized Lottery Ticket Networks. ECCV (12) 2022: 69-85 - [c6]David Byrd, Vaikkunth Mugunthan, Antigoni Polychroniadou, Tucker Balch:
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy. ICAIF 2022: 114-122 - [i8]Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Eugene Belilovsky, Irina Rish:
Gradient Masked Averaging for Federated Learning. CoRR abs/2201.11986 (2022) - [i7]David Byrd, Vaikkunth Mugunthan, Antigoni Polychroniadou, Tucker Hybinette Balch:
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy. CoRR abs/2202.09897 (2022) - 2021
- [c5]Vaikkunth Mugunthan, Ravi Rahman, Lalana Kagal:
BlockFLow: Decentralized, Privacy-Preserving, and Accountable Federated Machine Learning. BLOCKCHAIN 2021: 233-242 - [c4]Vaikkunth Mugunthan, Vignesh Gokul, Lalana Kagal, Shlomo Dubnov
:
DPD-InfoGAN: Differentially Private Distributed InfoGAN. EuroMLSys@EuroSys 2021: 1-6 - [i6]Vaikkunth Mugunthan, Vignesh Gokul, Lalana Kagal, Shlomo Dubnov:
Bias-Free FedGAN. CoRR abs/2103.09876 (2021) - [i5]Andreas Haupt, Vaikkunth Mugunthan:
Prior-Free Auctions for the Demand Side of Federated Learning. CoRR abs/2103.14375 (2021) - [i4]Vaikkunth Mugunthan, Pawan Goyal, Lalana Kagal:
Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners. CoRR abs/2106.05468 (2021) - 2020
- [c3]Vaikkunth Mugunthan, Anton Peraire-Bueno, Lalana Kagal:
PrivacyFL: A Simulator for Privacy-Preserving and Secure Federated Learning. CIKM 2020: 3085-3092 - [c2]Vaikkunth Mugunthan, Wanyi Xiao, Lalana Kagal:
Utility-Enhancing Flexible Mechanisms for Differential Privacy. PSD 2020: 74-90 - [i3]Vaikkunth Mugunthan, Anton Peraire-Bueno, Lalana Kagal:
PrivacyFL: A simulator for privacy-preserving and secure federated learning. CoRR abs/2002.08423 (2020) - [i2]Vaikkunth Mugunthan, Ravi Rahman, Lalana Kagal:
BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning. CoRR abs/2007.03856 (2020) - [i1]Vaikkunth Mugunthan, Vignesh Gokul, Lalana Kagal, Shlomo Dubnov:
DPD-InfoGAN: Differentially Private Distributed InfoGAN. CoRR abs/2010.11398 (2020)
2010 – 2019
- 2017
- [c1]Alexander Heifetz, Vaikkunth Mugunthan, Lalana Kagal:
Shade: A differentially-private wrapper for enterprise big data. IEEE BigData 2017: 1033-1042
Coauthor Index
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