Vladimir Vapnik recently gave a talk about a new theory of learning he is working on. The theory involves the concept of a “teacher” that provides the learning algorithm with privileged examples that can speed up learning. The inspiration came from the observation that humans require far more less examples to learn than current machine learning algorithms. His theory is that this phenomenon is partly due to the fact that the teacher controls the examples that are given to the student, while might also supply the student with privileged information, that even though might not be available at test time, it can be used to speed up training.

Quite interestingly, Joshua Tenenbaum has dealt with the same observation that humans learn much faster. His approach, called Bayesian Program Learning was already discussed in a previous post.

The talk can be found here: https://yandexdataschool.com/conference/2015/program/vapnik

 

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