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InfoResearchPeer-reviewed
Population Historical Information-Driven Evolutionary Multitask Neural Architecture Search
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Summary
The paper proposes HIMT-NAS, an evolutionary multitask neural architecture search algorithm. It records each generation's operation and topology information to guide the search and prevent redundant exploration, and it adjusts cross-task knowledge transfer probabilities by measuring task similarity. Experiments on MedMNIST, CIFAR-10, CIFAR-100, and Tiny-ImageNet show consistent gains over single-task NAS and recent MT-NAS methods.