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Haoyu Gu

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Open access Aug 2026

Prompt transfer for few-shot fault diagnosis in IIoT: a federated learning framework with tabular foundation models

In industrial internet of things (IIoT) deployments, condition monitoring data is rarely complete. Labeled samples are scarce, sensors drop out, signals are corrupted by noise, and what reaches the edge is often a sparse, distorted fragment of the ideal dataset. Federated learning preserves privacy, yet its standard fo...

Haoyu Gu, Diming Zhang, Shi-Chao Yi et al. · 0 citations
Open access Jul 2026

An Energy-Efficient Multi-Agent Reinforcement Learning Approach for Spark Job Scheduling in Mobile Edge Computing

Comparative tests with PPO, FIFO, FAIR and HAS baselines confirm that multi-agent reinforcement learning can well capture the intrinsic scheduling patterns of complex mobile environments, providing an adaptive and energy-efficient scheduling solution for practical IoT deployments.

Haoyu Gu · 0 citations

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