What is the purpose served by 1x1 convolutions in the papers?
    - Network in Network
    - GoogleNet
One reason which I came across for using them was to reduce dimensions. Are there any specific advantages for using them?

PS. I haven't come across any work which actually reduces dimension. They always have the same number of dimension as output.
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