Memory-aware federated learning for anomaly detection over IoT data streams

Authors

Publication Details

Journal
HAL (Le Centre pour la Communication Scientifique Directe)
Published
2026-06-29
Primary Topic
Data Stream Mining Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Memory-aware federated learning for anomaly detection over IoT data streams

Georgios Bouloukakis, Zahraa El Attar, Nikolaos Papadakis, Raafat Osman
HAL (Le Centre pour la Communication Scientifique Directe)
Data Stream Mining Techniques
article

Memory-aware federated learning for anomaly detection over IoT data streams

Georgios Bouloukakis, Zahraa El Attar, Nikolaos Papadakis, Raafat Osman
article en

Abstract

No abstract available for this paper.
HAL (Le Centre pour la Communication Scientifique Directe)
Partnerships for the goals
Openalex Percentile: Top 13%
Data Stream Mining Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.