Παρακολούθηση
Vaikkunth Mugunthan
Vaikkunth Mugunthan
PhD at MIT ; CEO/Co-Founder @ DynamoFL
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα mit.edu
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Παρατίθεται από
Παρατίθεται από
Έτος
PrivacyFL: A simulator for privacy-preserving and secure federated learning
V Mugunthan, A Peraire-Bueno, L Kagal
29th ACM International Conference on Information & Knowledge Management, 2020
322020
BlockFLow: Decentralized, privacy-preserving, and accountable federated machine learning
V Mugunthan, R Rahman, L Kagal
International Congress on Blockchain and Applications, 233-242, 2021
20*2021
SMPAI: Secure Multi-Party Computation for Federated Learning
V Mugunthan, A Polychroniadou, D Byrd, TH Balch
152019
Multi-vfl: A vertical federated learning system for multiple data and label owners
V Mugunthan, P Goyal, L Kagal
arXiv preprint arXiv:2106.05468, 2021
62021
Dpd-infogan: Differentially private distributed infogan
V Mugunthan, V Gokul, L Kagal, S Dubnov
Proceedings of the 1st Workshop on Machine Learning and Systems, 1-6, 2021
52021
Shade: A differentially-private wrapper for enterprise big data
A Heifetz, V Mugunthan, L Kagal
2017 IEEE International Conference on Big Data (Big Data), 1033-1042, 2017
52017
Bias-Free FedGAN: A Federated Approach to Generate Bias-Free Datasets
V Mugunthan, V Gokul, L Kagal, S Dubnov
arXiv preprint arXiv:2103.09876, 2021
42021
Collusion resistant federated learning with oblivious distributed differential privacy
D Byrd, V Mugunthan, A Polychroniadou, T Balch
Proceedings of the Third ACM International Conference on AI in Finance, 114-122, 2022
32022
Gradient Masked Averaging for Federated Learning
I Tenison, SA Sreeramadas, V Mugunthan, E Oyallon, E Belilovsky, I Rish
arXiv preprint arXiv:2201.11986, 2022
32022
FedLTN: Federated Learning for Sparse and Personalized Lottery Ticket Networks
V Mugunthan, E Lin, V Gokul, C Lau, L Kagal, S Pieper
European Conference on Computer Vision, 69-85, 2022
2022
A Practical Approach to Federated Learning
V Mugunthan
Massachusetts Institute of Technology, 2022
2022
Prior-Independent Auctions for the Demand Side of Federated Learning
A Haupt, V Mugunthan
arXiv preprint arXiv:2103.14375, 2021
2021
Utility-Enhancing Flexible Mechanisms for Differential Privacy
V Mugunthan, W Xiao, L Kagal
International Conference on Privacy in Statistical Databases, 74-90, 2020
2020
Improving the adaptability of differential privacy
V Mugunthan
Massachusetts Institute of Technology, 2019
2019
Poster: Novel strategies to calculate the privacy loss parameter in Differential Privacy
V Mugunthan, W Xiao, L Kagal
IEEE Symposium on Security and Privacy 2019, 2019
2019
Gradient Masking for Generalization in Heterogenous Federated Learning
I Tenison, SA Sreeramadas, V Mugunthan, E Belilovsky, I Rish
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