It also wouldn’t just be the random seed you’d need to memorize. You’d have to memorize all the training data and labels too. The scenario I gave was intended to be one where you were asked to study an algorithm for a while, and then afterwards operate it on a blank sheet of paper, given testing data. Even if you had the initialization seed, you wouldn’t just be able to spin up neural networks to make predictions...
It also wouldn’t just be the random seed you’d need to memorize. You’d have to memorize all the training data and labels too. The scenario I gave was intended to be one where you were asked to study an algorithm for a while, and then afterwards operate it on a blank sheet of paper, given testing data. Even if you had the initialization seed, you wouldn’t just be able to spin up neural networks to make predictions...
(just noting that same goes for a decision tree that isn’t small enough s.t. the human can memorize it)
Yes, exactly. That’s why the authors of tree regularization put large penalties for large trees.