Lesson plan
Proactive learning
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. "In real life, it is possible and more general to have multiple sources of information with differing reliabilities or areas of expertise. Active learning also assumes that the single oracle is perfect, always providing a correct answer when requested. In reality, though, an "oracle" (if we generalize the term to mean any source of expert information) may be incorrect (fallible) with a probability that should be a function of the difficulty of the question. Moreover, an oracle may be reluctant – it may refuse to answer if it is too uncertain or too busy. Finally, active learning presumes the oracle is either free or charges uniform cost in label elicitation. Such an assumption is naive since cost is likely to be regulated by difficulty (amount of work required to formulate an answer) or other factors." Proactive learning relaxes all four of these assumptions, relying on a decision-theoretic approach to jointly select the optimal oracle and instance, by casting the problem as a utility optimization problem subject to a budget constraint.
Article summary
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. "In real life, it is possible and more general to have multiple sources of information with differing reliabilities or areas of expertise. Active learning also assumes that the single oracle is perfect, always providing a correct answer when requested. In reality, though, an "oracle" (if we generalize the term to mean any source of expert information) may be incorrect (fallible) with a probability that should be a function of the difficulty of the question. Moreover, an oracle may be reluctant – it may refuse to answer if it is too uncertain or too busy. Finally, active learning presumes the oracle is either free or charges uniform cost in label elicitation. Such an assumption is naive since cost is likely to be regulated by difficulty (amount of work required to formulate an answer) or other factors." Proactive learning relaxes all four of these assumptions, relying on a decision-theoretic approach to jointly select the optimal oracle and instance, by casting the problem as a utility optimization problem subject to a budget constraint.
Key claims
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Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
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Key claims and bibliography are generated from the same tracked claims and sources as the article page.