output
20162025
most citedDeep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

539 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2020 · cs.LGShow all

2 papers · 2 filters

cs.LG2020★ 45 cited

Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things

Yi Liu, Ruihui Zhao, Jiawen Kang +3

Federated Edge Learning (FEL) allows edge nodes to train a global deep learning model collaboratively for edge computing in the Industrial Internet of Things (IIoT), which signific…

cs.LG2020★ 539 cited

Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

Yi Liu, Sahil Garg, Jiangtian Nie +4

Since edge device failures (i.e., anomalies) seriously affect the production of industrial products in Industrial IoT (IIoT), accurately and timely detecting anomalies is becoming…