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You seem to be describing hyperparameter optimization, which I seriously doubt CNNs are going to be used for anytime soon.
by argonaut 10y ago
You seem to be describing hyperparameter optimization, which I seriously doubt CNNs are going to be used for anytime soon.
- opticalflow 10y agoJust curious -- why would you think not?
- pedrosorio 10y agoIt has been done already: http://arxiv.org/abs/1502.05700 http://arxiv.org/abs/1502.05700 Edit: Although what they seem to describe is replacing GPs with neural networks in Bayesian optimization which is supposedly more efficient. Since the point of Bayesian optimization is to limit the number of times you have to evaluate a new set of hyperparameters, I am not sure how useful it is to "be able to scale" (i.e. even if maintaining the GP is O(n^3) with the number of evaluations, the costly part should be to evaluate the hyperparameters in the first place) but I haven't read the paper so they may show some high dimensional hyperparameter cases where performing a lot of evaluations pays off.