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Deutsch(DE) EvE: An Alternate Optimizer to Adam

EvE 优化器为神经网络搜索提供比 Adam 更快的替代方案

研究人员推出了一种名为 EvE (Evolutionary Explorer) 的新型优化器,旨在成为神经网络中超参数和架构搜索比 Adam 更快的替代方案。EvE 采用基于种群的差分进化方法,并结合了有针对性的 Adam 回退机制,显著降低了每次迭代的成本,同时保持了具有竞争力的性能。在对各种基准测试和神经网络任务的评估中,EvE 证明了搜索完成时间的缩短,以及与 Adam 相当或略低的最终质量,使其成为预算受限优化场景的有前途的工具。 AI

影响 EvE 可能会加速超参数调整和架构搜索,从而可能加快复杂 AI 模型的开发周期。

排序理由 该条目描述了一篇关于用于神经网络的新型优化算法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.NE (Neural & Evolutionary) 阅读 →

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EvE 优化器为神经网络搜索提供比 Adam 更快的替代方案

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该条目描述了一篇关于用于神经网络的新型优化算法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.NE (Neural & Evolutionary) TIER_1 Deutsch(DE) · Kalyanmoy Deb ·

    EvE:Adam 的一种替代优化器

    Adam and its variants dominate neural network training, but a single run only reveals whether a configuration works well after most of its budget is spent, a poor fit for hyperparameter or architecture search, where configurations must be ranked cheaply and pruned early. We intro…