PulseAugur
实时 07:39:32
实体 Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry

Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry

PulseAugur coverage of Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry — every cluster mentioning Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry across labs, papers, and developer communities, ranked by signal.

Show in brief
总计 · 30天
1
90 天内 1
发布 · 30天
0
90 天内 0
论文 · 30天
1
90 天内 1
层级分布 · 90 天
主题
情绪 · 30 天

1 天有情绪数据

最近 · 第 1/1 页 · 共 1 条
  1. TOOL · CL_247452 ·

    新理论解释浅层神经网络中的增量学习

    研究人员开发了一个新的理论框架,用于理解浅层神经网络中的增量学习。这项工作侧重于在标准初始化下,在正交多指标目标上训练的多项式宽度两层网络。研究结果表明,增量学习仍然发生,损失根据目标的厄米展开式顺序下降,低阶分量先于高阶分量被学习。