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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

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Abdullah Alhayan

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#federated learning Open access Sep 2026

FairPFL

FairPFL is a federated learning framework for IoT intrusion detection that treats fairness as an operational requirement: no device population should be left systematically under-protected by the shared detector. It combines a self-correcting fairness controller in the aggregation rule, a split personalization architecture, and a selective noise mechanism that perturbs only the shared backbone. This repository contains everything needed to reproduce the experiments. Datasets, trained checkpoints and result directories are not included; the sections below explain how to regenerate them.

Abdullah Alhayan · 0 citations
#federated learning Open access Sep 2026

FairPFL

FairPFL is a federated learning framework for IoT intrusion detection that treats fairness as an operational requirement: no device population should be left systematically under-protected by the shared detector. It combines a self-correcting fairness controller in the aggregation rule, a split personalization architecture, and a selective noise mechanism that perturbs only the shared backbone. This repository contains everything needed to reproduce the experiments. Datasets, trained checkpoints and result directories are not included; the sections below explain how to regenerate them.

Abdullah Alhayan · 0 citations

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