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A. Xenakis

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#machine learning Preprint Sep 2026

Constrained Bayesian Optimization for Hierarchical Federated Learning in IoT Networks for Plant Disease Classification

A constrained Bayesian Optimization framework for the efficient configuration of HFL deployments that captures user-defined trade-offs among energy consumption, execution time, and predictive performance, while explicit constraints ensure compliance with deployment-specific resource and accuracy requirements.

Athanasios Papanikolaou, Athanasios Tziouvaras, A. Xenakis et al. · 0 citations
Open access Jul 2026

Evaluation Framework for Cross-Layer Intrusion Detection Based on ML Approaches

This work proposed a modular weight-based framework that evaluates cross-layer Machine Learning (ML) IDS across multiple dimensions, namely, detection effectiveness and generalizability, data quality, and attack coverage and practical deployability, and applied this framework to the state-of-the-art cross-layer ML IDS...

Dimitrios Tasiopoulos, A. Xenakis, A. Lekidis et al. · 0 citations

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