学者揭示时序差分学习特征演化机制

1. 13:00
   arXiv 机器学习

   时序差分学习的特征演化分析

   该研究揭示了时序差分（TD）学习在有限宽两层 ReLU 网络下的特征演化机制，证明同时更新隐藏层与输出头的预测风险严格优于仅更新输出头，获得 2(d+1) 倍的总体二次响应提升。

Current heat 7·Comparable peak 10（Nov 4 14:00）·Comparable change, last 24 hours–

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