FEDERATED LEARNING IN SMALL-CELL NETWORKS: STOCHASTIC GEOMETRY-BASED ANALYSIS ON THE REQUIRED BASE STATION DENSITY

Federated Learning in Small-Cell Networks: Stochastic Geometry-Based Analysis on the Required Base Station Density

Recently, federated learning (FL) has been receiving great attention as an effective machine learning method to avoid the security issue in raw data collection, as well as to distribute the computing load to edge devices.However, even though wireless communication is an essential component for implementing FL in edge networks, there have been few w

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Impact of implementation interventions to improve substance use service delivery on recidivism among justice-involved youth

Abstract Substance use disorders (SUD) are prevalent among justice-involved youth (JIY) and are a robust predictor of re-offending.Only a fraction of JIY with substance use problems receive treatment.This paper describes the impacts of system-level efforts to improve identification and referral to treatment on recidivism of JIY.A cluster randomized

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