3 ms·

Hmm for those cases though, you would have to parametrize the training set to be able to optimally select the next training example in which case you're back to

• bmh100 12y ago
  > The key difference is that the teacher knows theta-star upfront and doesn’t need to explore. Based on this quote from page 1 and Wikipedia for "active learning" [1], I see the distinction in my examples as this: 1. In machine teaching, the teacher chooses the new observations to be presented. In active learning, the learner chooses new observations to be labeled. 2. In machine teaching, the availability of observations in general is controlled. In active learning, observations may be available but unlabeled, as in a cross-validation set. E.g., voting on which observation to have labeled. What is your understanding on these topics? [1]: https://en.wikipedia.org/wiki/Active_learning_%28machine_learning%29 https://en.wikipedia.org/wiki/Active_learning_%28machine_lea...