Mahdi Morafah — accepted AI-conference papers

2024

Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration

Mahdi Morafah, Vyacheslav Kungurtsev, Hojin Matthew Chang, Chen Chen, Bill Lin

NeurIPS 2024poster

Federated Learning (FL) has emerged as a promising paradigm for collaborative machine learning, while preserving user data privacy. Despite its potential, standard FL algorithms lack support for diverse heterogeneous device prototypes, which vary significantly in model and dataset sizes---from small…

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2023

Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces

Saeed Vahidian, Mahdi Morafah, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah +1

AAAI 2023technical

Clustered federated learning (FL) has been shown to produce promising results by grouping clients into clusters. This is especially effective in scenarios where separate groups of clients have significant differences in the distributions of their local data. Existing clustered FL algorithms are esse…

Cited by 69 Source ↗PDF ↗code ↗Scholar ↗