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20182020
most citedDeep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

539 citations · 559 across the 3 of their papers we have counts for

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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…