Redesigning decentralized ML algorithms: A systems view
Cancelled
Event details
| Date | 13.12.2021 |
| Hour | 13:00 › 15:00 |
| Speaker | Akash Dhasade |
| Category | Conferences - Seminars |
EDIC candidacy exam
exam president: Prof. James Larus
thesis advisor: Prof. Anne-Marie Kermarrec
co-examiner: Prof. Martin Jaggi
Abstract
soon available
Background papers
Communication-efficient learning of deep networks from decentralized data, by McMahan, H B., et al.
Tackling the objective inconsistency problem in heterogeneous federated optimisation, by Wang, J., et al.
Towards mitigating device heterogeneity in federated learning via adaptive model quantization, by Ahmed M. Abdelmoniem, Marco Canini
exam president: Prof. James Larus
thesis advisor: Prof. Anne-Marie Kermarrec
co-examiner: Prof. Martin Jaggi
Abstract
soon available
Background papers
Communication-efficient learning of deep networks from decentralized data, by McMahan, H B., et al.
Tackling the objective inconsistency problem in heterogeneous federated optimisation, by Wang, J., et al.
Towards mitigating device heterogeneity in federated learning via adaptive model quantization, by Ahmed M. Abdelmoniem, Marco Canini
Practical information
- General public
- Free