Submitted by eternal-abyss-77 t3_z9hff3 in MachineLearning
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Comments
eternal-abyss-77 OP t1_iygwbbr wrote
Got it bro, thanks
eternal-abyss-77 OP t1_iygx65a wrote
Bro, but let me ask you one more question, please bear with me.
If the result [ f(x)+f(x)+f(x)+f(x) ] >= result [ f(f(f(f(x)))) ]
(Result is feature map, features retained or extracted )
Can I conclude that both are same?
bacon_boat t1_iygxmve wrote
I think you need to check if you have a specific case in mind.
They are obviously not the same in general.
ML4Bratwurst t1_iygsjef wrote
No because stacking layers is basically what gives neural network their ability to extract high level features
Crafty_Primary_2776 t1_iyhy4dp wrote
That’s a good point. Actually slightly change your question leads to the problem of neural network width vs depth. Check these materials.
Do Wide and Deep Networks Learn the Same Things?
Universal approximation theorem.
bacon_boat t1_iygvgdf wrote
f(f(f(f(x)))) =/= f(x)+f(x)+f(x)+f(x)