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Is there any way to "scale up" the solution network for more dimensions?

For example, if i train on a a 100x100 image domain, with good results. So now I get a bigger budget to work with 200x200 images. There is no real way to leverage the good architecture from the 1st network. Is there ?

Can this be done as a ugly-hack and then be used as a seed into the architecture-search ?

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Not that I'm aware of. I could imagine a few things that you could try that might accomplish this, but I'm not aware of any published literature discussing the efficacy of such work.

You could do the naive thing, which would be to take your architecture and scale each layer size up (e.g. select an architecture on Cifar-10 and then scale it up to work on ImageNet). This is done in practice quite often, and seems to work well, but I'm not aware of any robust research done to validate the effectiveness of this.

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