Comments (2)
@Frank-Star-fn
我觉得可能还是要从以下的角度去解释这件事吧:
- 本质上我觉得还是数据量不够大吧。DCT比可学习的方式好可以理解为我们给他加了偏置(Inductive bias)进去,使得我们使用较小的数据量,或者不需要数据量直接利用DCT这种结构就可以work。(DCT也可以认为是一种人类经过几百万年优化出来的预训练权重)
- 如果数据量足够大,或者优化方式足够好,可学习的方式当然是包含DCT这一特例的,是有可能优化到DCT的吧
- DCT本身结构还是比较精妙的,比如它的低频已经能够很好地表达几乎所有的信号强度,并且这种能力是universal的而不是数据依赖的,并且DCT的基之间是相互正交的,因此不同的频段是没有冗余的;而学出来的基不能保证没有冗余,不能保证寥寥几个基就能表达大部分信息,也不能保证相互正交,他们还是数据驱动的,数据驱动还不一定数据集够大,优化方法够好
基于以上种种原因吧,我觉得可学习的目前还是没法达到DCT基的能力
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谢谢您的答复!
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