概括
最初的重量结构显著影响神经网络的学习. 低级权重促进丰富的学习,而高级权重导致惰的学习,除了基于任务对齐的例外.
科学领域:
- 理论神经科学理论神经科学
- 深度学习是一种深度学习.
- 计算神经科学是一种计算神经科学.
背景情况:
- 神经网络的学习动态受初始重量分布的影响,小差异与丰富的学习有关,大差异与惰的学习有关.
- 生物神经电路通常具有低级连接,与理论研究中常见的随机初始化形成鲜明对比.
结论:
- 最初权重的有效排名是神经网络中学习模式的关键决定因素.
- 这些发现对理解神经可塑性的代谢成本以及人工和生物系统中灾难性遗忘的风险有影响.
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