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.

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Showing cs.LGShow all

3 papers · 1 filter

cs.LG2024★ 11 cited

Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning

Haozhi Gao, Qianqian Ren, Jinbao Li

Contrastive representation learning is crucial in time series analysis as it alleviates the issue of data noise and incompleteness as well as sparsity of supervision signal. Howeve…

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…