I'm curious about the advantages of deeper networks in machine learning and artificial intelligence. Why are they considered better than shallower ones? What makes them more effective in handling complex tasks?
6 answers
ZenHarmonious
Wed Nov 06 2024
Parameter Efficiency is a concept that highlights the ability of deeper networks to achieve performance on par with or superior to wider networks, but with fewer parameters.
Andrea
Tue Nov 05 2024
In contrast, wider networks often require a larger number of parameters to achieve similar performance, which can lead to increased computational costs.
Raffaele
Tue Nov 05 2024
This efficiency is achieved through the reuse of features learned in earlier layers of the network.
SumoMighty
Tue Nov 05 2024
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Elena
Tue Nov 05 2024
By leveraging these previously learned features, deeper networks can reduce the number of parameters required to perform a given task.