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"A Review of Solving Non-IID Data in Federated Learning: Current Status" by Wenhai Lu, Jieren Cheng et al.

Federated learning (FL), as a machine learning framework, has garnered substantial attention from researchers in recent years. FL makes it possible to train a global model through coordination by a central server while ensuring the privacy of data on individual edge devices. However, the data on edge devices that participate in FL training are not independently and identically distributed (IID), resulting in challenges related to heterogeneity data. In this paper, we introduce the challenges gen...
Federated Learning Heterogeneous Data On Iid Data
Source: uow.edu.au

OASIS initiative provides $1.7 million for UCR research projects

UCR's Office of Research and Economic Development (RED) has announced over $1.7 million in competitive funding for faculty research projects through its Opportunity to Advance Sustainability Innovation and Social Inclusion initiative, known as OASIS. The projects range from probing the severity of COVID-19 infection in Riverside County, through sustainability and resilience in agriculture; to finding ways to mine lithium needed for electric car batteries from brine below the Salton Sea.
United States Salton Sea Riverside County Gregory Beran Haizhou Liu Kate Ostevik
Source: ucr.edu

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