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      <title>Posterior-guided neural architecture search</title>
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      <description>&lt;p&gt;本文提出一种后验引导的神经架构搜索方法，利用后验分布信息指导架构搜索过程，以更高效地探索候选架构空间。该方法通过建模架构的后验概率，将搜索导向更有前景的区域，从而在降低计算成本的同时提升最终模型的性能。相关工作在图像分类等基准任务上验证了其有效性，为自动化机器学习中的架构搜索提供了新思路。&lt;/p&gt;
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