5 citations · 7 across the 3 of their papers we have counts for
3 papers
Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks
Mahdi Morafah, Saeed Vahidian, Chen Chen +2
Though successful, federated learning presents new challenges for machine learning, especially when the issue of data heterogeneity, also known as Non-IID data, arises. To cope wit…
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles Between Client Data Subspaces
Saeed Vahidian, Mahdi Morafah, Weijia Wang +4
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…
Decentralized Asynchronous Non-convex Stochastic Optimization on Directed Graphs
Vyacheslav Kungurtsev, Mahdi Morafah, Tara Javidi +1
Distributed Optimization is an increasingly important subject area with the rise of multi-agent control and optimization. We consider a decentralized stochastic optimization proble…