Dzmitry Huba

According to our database, Dzmitry Huba authored at least 8 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

PAPAYA Federated Analytics Stack: Engineering Privacy, Scalability and Practicality.

Harish Srinivas, Graham Cormode, Mehrdad Honarkhah, Samuel Lurye, Jonathan Hehir, Lunwen He, George Hong, Ahmed Magdy, Dzmitry Huba, Kaikai Wang, Shen Guo, Shoubhik Bhattacharya

Proceedings of the 22nd USENIX Symposium on Networked Systems Design and Implementation, 2025

2024

Federated Analytics in Practice: Engineering for Privacy, Scalability and Practicality.

Harish Srinivas, Graham Cormode, Mehrdad Honarkhah, Samuel Lurye, Jonathan Hehir, Lunwen He, George Hong, Ahmed Magdy, Dzmitry Huba, Kaikai Wang, Shen Guo, Shoubhik Bhattacharya

CoRR, 2024

Confidential Federated Computations.

Hubert Eichner, Daniel Ramage, Kallista A. Bonawitz, Dzmitry Huba, Tiziano Santoro, Brett McLarnon, Timon Van Overveldt, Nova Fallen, Peter Kairouz, Albert Cheu, Katharine Daly, Adrià Gascón, Marco Gruteser, Brendan McMahan

CoRR, 2024

2023

Federated Ensemble Learning: Increasing the Capacity of Label Private Recommendation Systems.

Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu

IEEE Data Eng. Bull., 2023

2022

FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning.

Meisam Hejazinia, Dzmitry Huba, Ilias Leontiadis, Kiwan Maeng, Mani Malek, Luca Melis, Ilya Mironov, Milad Nasr, Kaikai Wang, Carole-Jean Wu

CoRR, 2022

PAPAYA: Practical, Private, and Scalable Federated Learning.

Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Federated Learning with Buffered Asynchronous Aggregation.

John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2019

Towards Federated Learning at Scale: System Design.

Kallista A. Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konecný, Stefano Mazzocchi, Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, Jason Roselander

Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, 2019